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Location: Barcelona; Cardiff, London or Remote (UK); London 🚀 We’re on a mission to make money work for everyone. We’re waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts , accounts for 16-17 year olds , a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save , invest and combine their pensions with us. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We’re not about selling products - we want to solve problems and change lives through Monzo ❤️ 📍 London or Barcelona | UK remote | 💰 £124,400 - 165,000 + Incentive Awards tied to your performance + Benefits | Technology — Data We’re looking for a Staff Data Scientist excited to help build the bank of the future. This is a senior individual contributor role for someone who combines deep technical expertise with strong commercial judgement and can apply both to Monzo’s most important and complex challenges. At Monzo, we’re building a bank that is fair, transparent and a delight to use. We’re growing extremely fast and have over 11 million customers in the UK. We’ve built a product that people love and more than 80% of our growth comes from word of mouth and referrals. Enable Monzo to Make Better Decisions, Faster We have a strong culture of data-driven decision making across the whole company. And we’re great believers in powerful, real-time analytics and empowerment of the wider business. All our data lives in one place and is super easy to use. 90% of day-to-day data-driven decisions are covered by self-serve analytics through Looker, which gives data scientists the headspace to focus on more impactful business questions and analyses. As a Staff Data Scientist, you’ll lead efforts on strategically important, business-critical problems. You’ll apply judgement in areas of organisational or technical complexity, steward initiatives end-to-end, and focus your hands-on contribution where it can create the greatest impact. You’ll be a trusted technical partner to senior leaders, raise the bar for Data Science across Monzo, and build capability in others through coaching, reusable approaches and clear standards. Our Data Science team ⭐ We are excited to be expanding and are hiring across our Data Science teams. Whether your interests lie in Borrowing, Growth, Payments, Fincrime, Wealth or Core, we are looking for versatile people who can contribute across squads and collectives. While we allocate teams after the interview process, we aim to match your skills and aspirations with the most suitable role. Throughout the process, you will meet team members from across our Data Science collectives, who will guide you through the opportunities available. Join us and be part of shaping our future! 🔑You’ll play a key role by... Shape and lead the data strategy for a large domain or collective, connecting customer and commercial goals to a clear portfolio of high-impact Data Science work Identify, frame and lead strategically important problems where the path is ambiguous, dependencies span teams, and decisions involve meaningful customer, commercial, regulatory or operational trade-offs Partner with senior leaders across product, engineering, ML, design, research, risk and operations, bringing an independent technical perspective that influences strategy and turns it into measurable outcomes Establish measurement strategies and metric maps that clarify how customer behaviour, product changes and business outcomes connect, enabling teams to test assumptions and make better decisions faster Set and evolve best practices for experimentation, causal inference, forecasting, optimisation and decision science, choosing methods that are proportionate to the decision and its risks Remain hands-on where your expertise is most valuable: exploring complex data, designing analyses and experiments, building models or prototypes, and resolving the hardest technical questions Steward critical data products and initiatives end-to-end, ensuring they are robust, well-governed, clearly documented and adopted by the people who need them Balance pace and analytical rigour, making pragmatic trade-offs while protecting the quality, reproducibility and interpretability of your work Raise Data Science standards across Monzo through technical direction, proposals, reviews, reusable methods and thoughtful challenge Coach and mentor data scientists and analytics engineers, using live projects and wider discipline initiatives to build sustainable capability beyond your own individual output 🤩 We’d love to hear from you if… You have an exceptional track record of leading complex, business-critical Data Science work from ambiguous problem framing through to measurable outcomes You have shaped strategy across a large product or business domain and can influence senior leaders through clear, independent judgement You bring deep expertise across several Data Science disciplines and can set the technical direction for work involving significant complexity, uncertainty or risk You repeatedly create clarity across organisational boundaries, resolve difficult dependencies and turn long-term strategy into decisive action You communicate complex ideas, assumptions and risks with clarity, and hold a consistently high bar for analytical quality, governance and reproducibility You remain a highly credible hands-on practitioner with SQL and Python, while raising standards and multiplying the impact of experienced colleagues The interview process: Our interview process involves: Recruiter Call Initial Call Technical assessment Final Interviews Business Fit/Collaboration Case Study Technical Interview Our average process takes around 2–3 weeks, but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process. We have some guidelines on using Artificial Intelligence (AI) to ace an application and interview at Monzo. You can read them here. For more insight into the hiring experience at Monzo, check out our blog post written by one of our Recruiters - Data Hiring at Monzo . What’s in it for you: 💰 £124,400 - £165,000 + Incentive Awards tied to your performance + Benefits ✈️ We can help you relocate to the UK or Spain ✅ We can sponsor visas 📍 This role can be based in our London or Barcelona offices, but we’re also open to distributed working within the UK (with ad hoc meetings in London). ⏰ We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team. 📚 Learning budget of £1,000 a year for books, training courses and conferences ➕ And much more - see our full list of benefits . If you prefer to work part-time, we’ll make this happen whenever we can — whether this is to help you meet other commitments or strike a great work-life balance. #LI-Remote Equal opportunities for everyone Diversity and inclusion are a priority for us and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog , 2026 Diversity and Inclusion Report and 2025 Gender Pay Gap Report. We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status. If you have a preferred name, please use it to apply. We don't need full or birth names at application stage 😊

Location: Tokyo, Japan About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Partners Solutions Architect on the Applied AI team at Anthropic, you will be a Pre-Sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP). You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy. Key Responsibilities Strategic Technical Partnership : Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities. Embed with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues. Joint Solution Development: Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment Customer Deal Support: Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance. Partner Ecosystem & Events : Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions, especially for technically native communities. Product Feedback: Validate and gather feedback on Anthropic's products and offerings, especially as they relate to partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy. Preferred qualifications 5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong presentation & technical communication skills with the ability to translate requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems Fluent in Japanese and English Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is looking for a Customer Marketing Manager to make sure our most important messages are backed by customers who can speak to them. This role works across regions and customer segments on special projects tied to the company's top priorities. When we launch a new model, feature, or initiative, you'll find the customers who can speak to it and get them on the record. We're looking for an excellent communicator who can turn customer stories into multiple formats that flex across channels. This often means working under compressed timelines and leading customer storytelling on some of the most important projects at Anthropic. You'll work closely with Product Marketing, Sales, Brand, Comms, Customer Marketing segment leads, and the writers on our team. The right person has done both product marketing and customer marketing, and has a reporter's nose for a good story. Key responsibilities Own the customer evidence strategy for the company's top priorities, deciding which claims need customer proof, which customers are best placed to back them up, and where we have gaps to close Bring what customers are telling us back to Product Marketing and Sales, so our messaging reflects what lands with buyers Stand up new programs as company priorities shift, setting the scope, the customer list, and the plan to ship quickly Lead the customer plan for major model and product launches, from which customers we engage with to how their voices show up in the announcement Partner with Brand and Creative on which customer stories anchor our campaigns and how we tell them Build proof point libraries and enablement around our key messages, so account teams know which story to use and when Shape the customer narrative our executives use in keynotes, posts, and customer conversations Prioritize customer asks when several teams want to tap the same customer, and work with Comms, Legal, and customer executives to get high-profile stories approved Minimum qualifications Can read a messaging doc and quickly spot what customer proof it needs and where the gaps are Are a strong writer and interviewer who can get a customer to say something specific and true, then turn it into a story people want to read Have supported product launches and campaigns with customer proof, often on tight timelines Have built sales enablement that sales teams kept using after launch week Are comfortable with technical products and can explain/write what a customer built, and why it matters, in plain language Know how to work across a lot of teams without formal authority, and can say “not yet” when a request doesn't fit the plan Have good judgment about when a story is ready and when it needs more work Enjoy moving between very different projects, sometimes in the same week Already use Claude to help with drafts and interview prep Preferred qualifications Have 7+ years in B2B marketing, with time in both product marketing and customer marketing Worked in AI or developer tools A background in journalism or editorial A background in Product Marketing or Messaging Written keynotes or LinkedIn posts for executives Run message testing or win/loss interviews to learn what buyers respond to Worked with Comms or analyst relations on announcements that featured customers The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $255,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the team Anthropic's Security Governance, Risk, and Compliance (GRC) team is the connective tissue that holds the company accountable to its security commitments. We translate regulatory, customer, and voluntary obligations into controls that teams act on, and give leadership a bird's-eye view of how well we're meeting them. We're building toward a fundamentally different kind of GRC: one that directs Claude, with the right humans in the loop, to challenge and evidence the performance of controls continuously rather than through periodic audits. Within Security GRC, Compliance & Audit Programs runs the integrated audit across our frameworks and maintains the Common Control Framework, the single set of controls that the whole program is built on. This role sits in Audit & Assurance and owns the framework and the assurance view across every control domain. About the role As part of the Security Audit & Controls team,  you will own the CCF across every control domain, from access and change management to logging, encryption, and people controls: which controls we have, what each one says, how each maps to the frameworks and commitments we hold, and whether each one is actually working. You'll work with control owners and GRC Partners to draft and validate control descriptions and activities that describe reality rather than policy intent, build the monitoring that shows operating effectiveness continuously instead of once a year, and drive what monitoring finds to closure with control owners. Building with Claude is a normal part of the job: drafting and mapping controls, testing evidence, and monitoring control health, with you deciding where human judgment stays in the loop. This is an individual contributor role for someone who works well independently, writes clearly, and gets satisfaction from a control set that is accurate, tested, and trusted by auditors and engineers alike. Key responsibilities Own the Common Control Framework: the canonical control set, its mappings to SOC 2, ISO 27001/42001, HIPAA, FedRAMP, and customer commitments, and the change process for adding, retiring, or rewording controls Draft and validate control descriptions and control activities with control owners, so each control states who does what, how often, in which system, and what evidence proves it Design and run continuous monitoring of control efficacy: define the metrics and automated tests that show operating effectiveness, tune out false positives, surface failures to owners before an auditor does, and build the controls maturity model that shows where each control domain stands and what it takes to move up a level Verify remediation and carry it into steady state: GRC Partners lead remediation in their domains and control owners implement the fixes. This role advises on control design and implementation, confirms fixes against what the auditor actually asked for, and keeps one source of truth for control and finding status. Once a fix holds, it works with the partner to standardize the evidence pull and, where appropriate, automate it or build continuous Map new frameworks and commitments onto the CCF as we commit to them, and support gap assessments when a new framework, certification, product, or entity comes into scope, using the CCF as the baseline and writing the requirements for each delta Support the integrated audit and customer audits: readiness checks, walkthrough preparation, evidence request lists, and the readout of external findings back to GRC Evaluate evidence reliability, including the completeness and accuracy of system-generated reports and AI-generated evidence, and set the standard for what audit-ready evidence looks like here Build with Claude: automate control mapping, evidence testing, and monitoring, and verify machine-drafted control language before it becomes the record Minimum qualifications Several years in IT audit, security compliance, or controls assurance, including hands-on ownership of a control framework or control library across more than one framework (for example SOC 2, ISO 27001, FedRAMP, HIPAA) Working command of audit mechanics: scoping, walkthroughs, sampling, design versus operating effectiveness, deficiency evaluation, and evidence reliability Experience writing control descriptions, control activities, and test procedures that other teams and external auditors relied on Experience with continuous controls monitoring or automated evidence collection, whether you built it, ran it, or audited it Enough technical fluency to read a runbook, a configuration, or a pipeline definition and judge whether it enforces what the written control claims Clear writing, because your control language and status reports are what auditors, engineers, and leadership work from Ability to get control owners and partner teams to prioritize and close work without having authority over them Preferred qualifications Have designed or rebuilt a common controls framework and led the remapping of existing frameworks onto it Have stood up continuous controls monitoring or automated evidence programs and can speak to coverage, false-positive rates, and what changed as a result Have applied LLMs to assurance work, such as control drafting, framework mapping, evidence testing, or monitoring Have defined or assessed controls for AI systems or agents operating in production, or for home-built internal systems Have provided requirements for a homegrown GRC platform and worked with the engineers who build it You don't need to Have done everything on this list. The scarce combination this role exists for is framework ownership plus the judgment to tell whether a control actually works Write production code. The bar is fluency sufficient to read, query, and challenge Hold every certification. CISA, CISSP, or similar are welcome and not required Have prior AI-industry experience Logistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas. However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Deadline to apply: None. Applications will be received on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $270,000 — $345,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. The RL Scaling team works on how RL scales: what happens to throughput, stability, and learning efficiency as models get larger, episodes get longer, and compute grows by orders of magnitude, and what has to change in our algorithms and systems to keep getting returns from that scale. This role sits squarely across research and engineering. You'll develop next-generation architectures and RL algorithms, take them from a small-scale result to a frontier-scale run, and understand every place they behave differently along the way. You'll build the systems that set how fast the team can iterate: how many experiments, at what scale, and how quickly we can trust the results. And you'll work on Anthropic's largest and fastest RL runs, where the gap between a good idea and a working one is often a problem no one has solved yet. Key responsibilities Study how RL training and sampling scale with model size, context length, and compute, and find the algorithmic and systems changes that keep scaling efficient Develop next-generation model architectures and RL algorithms, and make them run efficiently at frontier scale Take promising small-scale results to frontier-scale runs, and diagnose why they behave differently when they get there, whether the cause is numerical, algorithmic, or systemic Build the experimental infrastructure that sets research velocity: fast, reproducible comparisons of architecture and algorithm variants at meaningful scale Own end-to-end performance of our largest RL runs, from research code down to the hardware Build performance and cost models for proposed architecture and algorithm changes, and use them to decide which ideas get scaled Investigate training dynamics at scale, including instabilities, divergence, and throughput regressions, and trace them to root cause Minimum qualifications Deep familiarity with modern transformer language models, including their architecture, training dynamics, and the behavior of large-scale optimization Hands-on experience training large models in a distributed setting, including the tradeoffs between data, tensor, and pipeline parallelism A track record of original technical work in ML training or systems, such as new methods, architectures, or optimizations, demonstrated through research, open-source, or production impact Ability to design rigorous experiments at scale, including baselines, ablations, and enough statistical care to trust a result that costs real compute Ability to reason quantitatively about the compute, memory, and communication costs of a model or algorithm Strong programming skills in Python and JAX or PyTorch, and comfort reading and changing code at every layer of the stack Preferred qualifications Research experience in reinforcement learning, optimization, or large-scale training, published or otherwise Experience developing RL algorithms for language models Experience with scaling laws or other quantitative models of training efficiency Experience designing or modifying transformer architectures beyond standard configurations Experience scaling training to large fleets of accelerators and debugging the problems that only appear at scale Deep understanding of numerics in large-scale training, including low-precision formats and sources of instability Familiarity with how GPU or TPU performance characteristics shape architecture and algorithm choices Experience with C++ or Rust Representative projects Characterize how a new RL algorithm's throughput and learning efficiency change from small models to frontier scale, and fix what breaks Develop a new attention variant, get it working at full scale, and measure how its quality and throughput compare to the baseline Prepare our next largest-ever RL run: find what breaks when model size, context length, and compute all grow at once, and fix it before launch Trace a loss instability that only appears past a certain scale to its root cause, and work out whether the fix belongs in the algorithm, the numerics, or the system Build a model that predicts the throughput and cost of a proposed architecture change before anyone writes the kernel The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is an unusually demanding distributed system. Training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts, exchange data continuously, and have to keep making progress while hardware fails, load shifts, and the research changes underneath them. How well that system holds together determines how much of our compute turns into learning, and how quickly the team can try the next idea. As a Research Engineer on the Distributed Systems team within RL Engineering, you'll work on whatever part of that system is the current limit. That might be scheduling and placement, data movement between components, running large numbers of sandboxed environments, storage and checkpointing, networking, fault tolerance, autoscaling, or the observability that tells us what a run is actually doing. We're looking for generalists: engineers who can move between these layers, reason from first principles about a system they haven't seen before, and pick the problem that matters most rather than the one closest to their prior experience. Our system changes as fast as the research does, correctness under failure matters as much as throughput, and the best solutions often come from understanding the ML workload well enough to know which guarantees it actually needs. Strong candidates have built and run large distributed systems, care about getting the details right, and want to apply that experience to a workload that is very large, very heterogeneous, and changing quickly. Key responsibilities Design, build, and operate the distributed systems that run RL at scale, across training, sampling, and environment execution Find and remove whatever currently limits the system, whether it's scheduling, data movement, storage, networking, or coordination Build fault tolerance into every layer: failure detection, isolation, and recovery that keep long-running jobs making progress without human intervention Design resource management and autoscaling so that compute follows demand as a run's needs shift Build observability that makes it possible to understand what a run is doing and why it slowed down, stalled, or produced unexpected results Build automation that detects and remediates common problems, and design interfaces that let engineers and automated tools operate runs safely Work with researchers and performance engineers to make sure systems changes preserve training correctness and don't introduce subtle nondeterminism Remove classes of failure at their source through incident review, testing, and redesign, and write clear design documents for what you build Minimum qualifications Strong software engineering skills in Python and at least one systems language such as Rust, C++, or Go Experience designing, building, and operating large-scale distributed systems in production Deep understanding of distributed systems fundamentals, including consistency, coordination, consensus, failure modes, and recovery Ability to reason quantitatively about throughput, latency, and resource costs across compute, memory, storage, and network Experience debugging complex failures across many hosts and services, including failures you can't reproduce locally Strong written communication, including design documents and incident writeups Preferred qualifications Experience running ML training or inference infrastructure at scale Experience across several layers of the stack, such as scheduling, storage, networking, and orchestration Experience building schedulers, autoscalers, or resource management systems Experience with container orchestration such as Kubernetes, and with sandboxed or virtualized code execution at scale Experience with high-performance networking, RDMA, or collective communication libraries Experience building observability or automated remediation for large fleets Experience with async Python frameworks such as Trio or asyncio Familiarity with reinforcement learning or large language model training workloads Representative projects Design a scheduler that places training, sampling, and environment work across a heterogeneous cluster while respecting network topology and failure domains Build a failure detection and recovery system that lets a long-running job survive host and network failures with minimal lost work Scale environment execution substantially without increasing tail latency for the training step Design an autoscaling policy that rebalances compute across components as a run's bottleneck shifts Build a diagnostics system that explains why a run's throughput dropped and proposes a fix Trace a rare data corruption bug across many services to a race condition in a recovery path, and redesign the path so the class of bug can't recur Design the operational interface for a run so that automated tools can safely diagnose and adjust it under human oversight The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote-Friendly (Travel Required) | San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Data Center Security Engineering (DCSE) secures Anthropic's data center footprint; this role covers how the sites are designed and built to be secure. Much of that footprint is designed and built with partners, so a site's security is decided early: in what Anthropic hands the people who build it, and in how rigorously the delivered systems are tested against it. You'll design and specify the physical security systems for a site: perimeter and vehicle barriers, intrusion detection, video, security lighting, and the site penetrations and utility entry points that bypass them. Design firms and integrators produce the site drawings and install; you specify, review, and verify. You'll write the performance requirement and verification method behind each control, review every site design against them at each stage with redlines a design team can act on, test in the field that what was built performs as specified, and re-verify post-acceptance changes. This is a foundational role. You'll own Anthropic's physical security reference design package (typical details, reference drawings, schedules, and test procedures) in the form partners build from, and keep it current against each site's threat basis and the sites actually being built. You'll set the technical position for a site and decide what applies where; where a requirement can't be met as written, you'll engineer the compensating control and document the deviation. You'll work with the rest of DCSE, with Anthropic's design, construction, and real estate counterparts, and directly with the vendors who build to the package. We use Claude throughout our engineering workflow and expect you to as well. The same seat covers the team's security operations control rooms. You'll set their design and operational requirements and accept delivered systems against them, working day to day alongside the team's platform engineers, who own the software and compute that run in them. This role involves regular travel to data center sites. These are critical services, and this role participates in an on-call rotation for them. Key responsibilities Produce a vendor-ready design package for perimeter barriers and hostile vehicle mitigation, intrusion detection and its zoning, video coverage, security lighting matched to camera performance, and penetration protection: performance specifications, typical details and reference drawings, and device and zone schedules, written so a design firm can build to them and a test can prove them Define the per-site engineering basis: which requirements apply to a site based on its risk profile and the threats it faces, with compensating controls and documented deviations Write the acceptance criteria and test methods: the verification method behind each requirement and the evidence a site must produce to pass acceptance Set standoff, structural hardening, and site layout criteria for new designs, tied to the threat basis they derive from Run field verification: commissioning and acceptance testing of perimeter, detection, video, and lighting against performance criteria (detection coverage tests, photometric measurements, video quality checks) Write the operational and design requirements for security operations control rooms: console layout, wall versus workstation content, supervisor placement; room network, power, backup, and resilient communications to the team's segmentation and hardening baseline Own control room acceptance: factory and site acceptance criteria written before the build, then accept or reject delivered systems (video wall, consoles, cabling, fit-out) against them Minimum qualifications Have designed or specified physical security systems (perimeter barriers, intrusion detection, video, security lighting) for campus-scale sites: multiple buildings, a secured perimeter, many detection zones Read and produce construction documents (site plans, civil and electrical drawings, device schedules, submittals) using standard design and markup tools such as AutoCAD, Revit, or Bluebeam, and find what is missing as readily as what is wrong Write performance requirements that are testable: each states what must be true, how it will be verified, and what evidence shows it Have run commissioning and acceptance tests against performance criteria and rejected work that did not meet them Derive requirements from a threat basis rather than a product catalog: you can say which adversary a control stops and where the next weakest point is Have owned an engineering domain where you set the approach, chose what applied to each site, worked directly with vendors, and answered for the result Preferred qualifications Experience carrying a physical security design from construction documents through construction to acceptance testing Experience engineering the security scope of colocation or partner-delivered facilities Working knowledge of published standards for standoff, hostile vehicle mitigation, and intrusion detection zoning Photometric and video quality measurement experience Control room, AV, or network design experience: console layouts, video wall systems, resilient communications Experience using AI-assisted tooling for drafting and review as a core part of your workflow The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Almaty, Kazakhstan Workplace: OnSite WHY WORK AT HIGGSFIELD AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. WHO WE ARE LOOKING FOR Everyone at Higgsfield is an A-player. We’re looking for teammates who bring: - High IQ, energy, and agency. - Extreme autonomy, and ownership. - The ability to move fast, experiment constantly, and learn even faster. - Resilience under pressure and readiness for an always-on environment. - A balance of data-driven judgment and creative intuition. - The drive to raise the standard for the entire team, not just yourself. WHAT YOU WILL WORK ON - Create compelling content for our official website — including blog posts, press releases, feature articles, and thought leadership pieces on Generative AI — designed to engage a global audience. - Drive PR and media communications, building and maintaining strong relationships with key media contacts in the US and Europe, influencers, and analysts to maximize visibility and coverage. - Support PR for Kazakhstan and Central Asia: build relationships with regional tech and business media, coordinate local announcements and interviews in Russian and English. - Collaborate cross-functionally with Product, B2B, and Growth teams to understand new features and innovations, then translate them into compelling launch stories and product blogs. - Build scalable content and PR processes that automate workflows, enhance efficiency, and deliver measurable growth across SEO and earned media channels. YOUR MUST HAVES - Proven track record of measurable copywriting results. - High IQ and elite problem-solving skills. - Tier-1 university degree & high GPA. - Excellent writing & analytical skills with marketing impact. - Fluent English. - Ability to thrive in a startup environment. NICE TO HAVES - Experience in marketing copywriting, with a deep understanding of what makes content clear and effective. - Experience working in early-stage and fast-growing startups or teams. - International PR agency background THE DEAL - Competitive salary in USD. - On-site role in Almaty office. - Full-time position.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's go-to-market engine runs on Salesforce: how leads become pipeline, how deals are tracked and forecast, how customers renew and expand, and how partners work alongside our sellers. As a Business Systems Analyst, you'll be responsible for how one of those core motions is represented in system, and a trusted partner to GTM leadership when they want to change how it works. We're looking for someone who operates at the intersection of three things: a strategist who can sit with GTM leaders and shape how they want to understand their part of the business, an analyst who can turn that into rigorous process and data design, and a builder who's comfortable enough in Salesforce to ship meaningful parts of it themselves. You can move fluidly between whiteboard, requirements doc, and admin console. You'll partner deeply with RevOps on the operating model and with our Salesforce developers on anything that needs code. Where you might sit We're hiring across several parts of the customer lifecycle. Placement depends on your background and where you can have the most impact. Opportunity Acceleration: Owns how deals are tracked, forecast, and credited in Salesforce, from stage design and forecasting to the ownership and team structures behind them. You'll partner with sales leadership to make pipeline something everyone can trust and sellers can work quickly. Lead-to-Pipeline: Owns how leads, inbound demand, and BDR outreach become qualified pipeline: lifecycle stages, routing and ownership, handoff rules, and the tools BDRs and sellers work in every day. You'll partner with BDR, marketing, and sales leadership to make the path from first touch to open opportunity faster and easier to measure. Post-Sales: Owns the systems behind renewals, expansion, and customer coverage: how post-sale opportunities are created, forecast, and worked by account management and customer success. You'll give post-sales leaders a clear, trustworthy view of the customer base and the tools to act on it. Partnerships: Owns how partner-sourced and co-sell deals are registered, attributed, and worked alongside our sellers, including the partner-facing processes and reporting leadership relies on. You'll help turn a fast-growing channel into a motion the business can measure and scale. Key responsibilities Own the design of your core funnel domain in Salesforce: lifecycle stages, process, exit and handoff criteria, key fields, and the automation and guardrails that keep the data trustworthy Partner with GTM leadership on how their motion runs and how they want to see it, and make the tradeoff calls on what teams enter versus what insight that data unlocks Partner with RevOps to systematize how GTM teams are structured, assigned, and credited: ownership, routing, coverage, splits, and the territory and role structures those depend on Operationalize the methodology in system, turning frameworks and process discipline into fields, validation, scoring, and in-context guidance that people actually use Act as data-model steward for your domain and its closest neighbors: the named approver for new fields, automation, and integrations touching those objects, and the keeper of why each one exists Build and ship declarative solutions yourself where that's the right call, and write specs clean enough that our developers can build the rest without five rounds of clarification Own the seams to the neighboring stages of the customer lifecycle (lead handoff, opportunity, quote-to-cash, renewal, partner attribution) so the experience is coherent end to end even where the build sits with another team Evaluate and configure tooling that accelerates the motion: routing, activity capture, sequencing, deal inspection, account planning Run discovery, UAT, enablement, and adoption measurement for everything you ship; help raise the bar for how BSA work is done on this team Minimum qualifications Experience in GTM/Revenue systems as a Business Systems Analyst, Sales Systems Lead, or RevOps Systems role, with real ownership of work in a core funnel domain such as lead management, opportunity and pipeline, renewals and account management, or partner channel Experience designing and rolling out a lifecycle, process model, or forecasting motion at a fast-growing company, owning it from discovery through enablement and adoption Credibility with GTM stakeholders: you've been in the pipeline review, forecast call, or planning session, and you can push back when there's a better answer Hands-on Salesforce skills, with comfort building meaningful parts of your own solution (Flow, validation, assignment and routing, page and Path design) and specs that make the handoff to developers clean Crisp communication across GTM teams, leadership, RevOps, and engineers, adjusting altitude for each Preferred qualifications 5+ years of experience in GTM/Revenue systems roles Salesforce Administrator certification Advanced Administrator, Business Analyst, or Sales Cloud Consultant certification Experience partnering with RevOps or Sales Strategy on team-structure questions (ownership, routing, splits, territory) and turning those decisions into working system design Experience across more than one part of the customer lifecycle, such as lead, opportunity, renewal, or partner Curiosity about AI-assisted systems work and eagerness to fold it into how you design, build, and document; prior hands-on use is a strong plus The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $270,000 — $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking an experienced public opinion researcher to build and expand Anthropic's in-house polling and research function. This role will be fundamental to understanding how key audiences — from policymakers and third-party groups to the general public — perceive and respond to Anthropic's policy positions, messages, and campaigns. This is a foundational role: you'll establish the research function from the ground up, with high autonomy and limited precedent. The Central Policy team sits at the operational heart of Anthropic's policy function — distinct from government relations and communications, but essential to enabling both. You'll work cross-functionally to ensure our policy and communications strategy is grounded in a rigorous understanding of stakeholder sentiment. The polling insights you generate will directly feed into high-visibility campaigns and will be a key asset in our policy efforts in Washington and beyond. Anthropic is equal parts research lab, policy think-tank, and technology startup. We care deeply about the safe development of AI systems and build partnerships with governments through proactive, opinionated, substantive policy conversations. This role offers a unique opportunity to be at the forefront of AI policy, bringing rigorous research discipline to policy strategy. Success in this role means establishing trusted relationships with leading polling firms around the world, delivering high-quality research on a regular cadence, and becoming the internal expert on how key audiences perceive AI, Anthropic, and Anthropic's positions and messages. You'll translate polling insights into strategic recommendations that measurably improve campaign effectiveness, and build scalable processes that allow the function to grow efficiently as demand increases. Key responsibilities Develop a comprehensive strategy for our in-house political research function that aligns with Anthropic's policy goals Identify, evaluate, and establish relationships with leading research and polling firms, ensuring coverage across demographics, geographies, and political perspectives Conduct detailed, proactive research to test core messages, policy proposals, and campaign themes, and to evaluate Anthropic's brand perception and performance Execute rapid-response polling to quickly assess Anthropic's messaging strategy in response to external events, policymaker actions, competitive developments, or emerging opportunities Work with external affairs colleagues (federal, state, and international) and policy communications to identify research priorities, interpret findings, and translate insights into actionable strategic recommendations Develop and maintain a knowledge management system for polling data, insights, and recommendations that ensures findings are accessible and actionable Manage polling vendors at scale, including vendor performance management Participate in strategy sessions and provide thought partnership on the design of messages, policy proposals, and campaigns ahead of polling and testing Create clear, compelling deliverables that distill polling findings into insights and recommendations Identify opportunities to build and scale the polling function over time, including staffing needs, process improvements, and capability expansion Track and report on the impact and utility of research, measuring how insights translate into more effective campaigns and strategic decisions Minimum qualifications Experience designing and executing public opinion research, including survey and questionnaire design, sampling approaches, and message testing Ability to analyze quantitative and qualitative polling data and translate findings into clear, decision-ready written recommendations Experience selecting, briefing, and managing external polling or research vendors Strong writing and presentation skills, including distilling complex research for senior, non-technical audiences Preferred qualifications 8+ years of professional experience in political or public opinion research, ideally spanning multiple campaign cycles and policy environments Corporate public affairs experience, ideally in a highly scrutinized or regulated industry Strategic thinking that spots emergent issues, identifies and tests the right messages, and translates those insights into tactical recommendations A track record of building relationships with vendors, external experts, and complex stakeholder ecosystems Strong organizational skills, with the ability to manage multiple projects simultaneously, maintain clear priorities, and deliver on tight timelines Comfort operating in ambiguous environments, taking ownership of problems, and proactively driving initiatives with limited precedent A resourceful, collaborative working style and genuine commitment to being a strong teammate Passion for AI policy and alignment with Anthropic's safety mission and commitment to responsible AI development The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $230,000 — $265,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: As a Field Executive Architect, you will serve as Anthropic's senior technical voice with our most strategic customers. You'll engage directly with C-suite executives and senior technical leaders at the world's largest enterprises to understand their business, align stakeholders around a clear vision for how AI fits into their strategy, and create momentum toward adoption of Anthropic's products. This is not a hands-on-keyboard engineering role. Your job is to walk into a room full of executives, quickly understand their business and technical landscape, and help them see a clear path forward with Claude. You'll then partner with Sales and Applied AI teams to ensure that vision translates into execution -- checking in on high-momentum accounts, maintaining executive relationships, and keeping deals on track. Internally, you'll serve as a sponsor for enterprise customer needs, working with Product to ensure that what matters most to our largest accounts is heard and prioritized. You'll bring deep experience in enterprise technology and a track record of operating at the intersection of business strategy and technical execution. Whether you've been a CTO, VP of Engineering, Field CTO, or a world-class senior technical salesperson, what matters is that you've seen how large organizations make technology decisions and can meet executives where they are -- with credibility, clarity, and conviction. Responsibilities: Engage directly with C-suite and senior technical leaders at Anthropic's largest and most strategic accounts, aligning business and technical stakeholders around a clear vision for AI adoption Prepare for and lead high-stakes customer engagements -- executive briefings, EBCs, on-site workshops -- that change the trajectory of key accounts at critical inflection points Partner with Sales and Applied AI teams before and after engagements to game plan approach, debrief on outcomes, and ensure the vision carries through to execution Lean in on high-momentum accounts after initial engagement, maintaining executive relationships, providing strategic guidance to the Sales and Applied AI teams, and sustaining deal momentum Serve as an internal sponsor for enterprise customer needs, translating field feedback into clear priorities for Product and ensuring the most important enterprise requirements are heard and acted on Bridge the gap between our field organization and Product org -- helping each side understand the other's priorities, constraints, and roadmap Travel regularly to customer sites for executive engagements, workshops, and strategic account meetings You may be a good fit if you have: 15+ years of experience in enterprise technology, with significant time spent in senior technical leadership or senior technical sales roles (CTO, VP of Engineering, Chief Architect, Field CTO, or similar) A track record of engaging credibly with C-suite executives and senior technical leaders at large enterprises -- you can hold the room and earn trust quickly Deep understanding of how large organizations evaluate, buy, and scale technology -- you've seen the inside of these decisions from a leadership seat or from the sales side of the table Enough technical depth to understand modern AI systems and their enterprise applications, and enough business acumen to connect technical capabilities to business outcomes Experience translating between technical and business audiences -- you can make complex topics clear and compelling for both Strong opinions about what makes enterprise technology adoption succeed or fail, informed by having led or closely advised these efforts The ability to navigate ambiguity and move fast in a rapidly evolving market -- you're comfortable operating without a detailed playbook and building the plane while flying it A collaborative mindset -- sales at Anthropic is a team sport Excitement about AI's potential to transform how enterprises operate, and a genuine desire to help customers succeed with it Willingness to travel regularly for customer engagements The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $400,000 — $500,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Tasks: — Lead and execute core 0-to-1 initiatives in cutting-edge domains such as Agentic AI. — Translate high-level strategic vision into concrete execution roadmaps, driving rapid implementation from prototype to production. — Architect scalable solutions and drive critical milestones to position the new department for rapid growth and potentially a spin-off to attract institutional backing. Requirements: — Based in Europe or the Americas (or open to relocate/remote arrangements). — High-agency builder mindset, with proven domain expertise and the drive to take extreme end-to-end ownership. — Excellent verbal and written communication skills in English. Conditions: — 100% remote work. — Full-time employment. Additional information: — Maximum ownership: Complete autonomy to architect systems, drive strategy, and build from 0 to 1 without corporate red tape. — High-growth environment focused on strong market validation and scalable traction. — Elite team: Report directly to the department founder and collaborate with a world-class team. — Competitive compensation with equity upside.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Data Center Security Engineering (DCSE) owns physical security across Anthropic's data center footprint: the sites, the hardware inside them, and the supply chain that delivers it. The Security Fusion Platform is where physical security signals from across that footprint are correlated and put in front of the analysts who act on them. It carries continuous monitoring, audit evidence, metrics, and analyst response, along with the classification and analytics pipelines that turn sensor data into events. You'll build and own the platform analysts work from. This is a foundational role. You'll build the software platform that carries a signal from source to analyst decision, ship its first versions, and keep them running in production. The sensors and systems at each site belong to other DCSE engineers; you define the event contract their owners deliver to, and you build the classification and analytics pipelines that run over what those sources produce. Physical security systems engineers own the operations spaces; you own the software that runs in them. You'll work alongside engineers focused on the sites themselves. What you lead, you own end to end: the design, the technical approach, and the result in production. You'll work with external vendors and integrators, setting requirements and acceptance criteria for what you own and deciding what the team builds itself. We use Claude throughout our engineering workflow and expect you to as well. This role involves regular travel to data center sites. No security clearance is required. These are critical services, and you'll take part in on-call for them. Key responsibilities Design and build the event bus and normalized event schema: source identity, sequencing, health state, and the adapter contract that owners of each sensor and system feed build to, plus adapters where needed Build correlation and alerting: the rules and services that turn events from independent sources into alerts an analyst can act on Build the classification and analytics pipelines: computer vision and multi-sensor fusion, with results landing on the event bus Build analyst surfaces: the queue, escalation tooling, dashboards, camera viewers, and video wall content a 24/7 watch works from, plus video analytics integration so camera streams arrive on the bus as events Deliver audit evidence: durable, tamper-evident event history, evidence exports, and the retention and access controls around them Instrument metrics and self-monitoring: detection rates, nuisance ratios, alert aging, time to resolve; heartbeats and loss-of-telemetry alarms on every feed, tested fail-secure behavior, and change audit on every rule Deploy across sites: site-local components, central services, and the sync that keeps configuration, rules, and state consistent, then commission each site and hand over to the analysts Specify the compute the platform runs on (servers, storage, and the platform's network segment) to the team's segmentation and hardening baseline Write requirements and acceptance criteria for what vendors and integrators deliver, review deliverables against them, and make the call on accepting or rejecting the work Minimum qualifications Have built and run event-driven backend systems in production Are proficient in at least one backend language such as Python, Go, or Rust, and have worked with a message bus or event streaming system such as Kafka Have owned a system end to end: set the design, made the tradeoffs, shipped it, and answered for it in production Have integrated with external systems you did not control (vendor APIs, on-prem appliances, video platforms, building systems) and designed for a life beyond any one vendor Have directed vendor or integrator work: written requirements and acceptance criteria, reviewed deliverables against them, and decided what gets accepted Design for the failure you won't see coming (a silent feed, a lost network path, a replayed event, a de-tuned rule), know how your system behaves when a source lies or goes quiet, and test for it Build tools for people who use them under pressure and iterate with those operators Preferred qualifications Experience building or operating a security operations platform (SOC, physical security operations, or the detection engineering behind one) Experience building ML or computer vision inference pipelines over video and sensor streams PSIM (physical security information management) or VMS (video management system) integration experience, or familiarity with physical access control and building systems data Experience producing evidence for auditors or assessors: log integrity, retention, chain of custody Experience using AI-assisted development tooling as a core part of your workflow The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Seoul, South Korea About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Partners Solutions Architect on the Applied AI team at Anthropic, you will be a Pre-Sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP). You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy. Key Responsibilities Strategic Technical Partnership : Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities. Embed with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues. Joint Solution Development: Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment Customer Deal Support: Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance. Partner Ecosystem & Events : Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions, especially for technically native communities. Product Feedback: Validate and gather feedback on Anthropic's products and offerings, especially as they relate to partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy. Preferred qualifications 5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong presentation & technical communication skills with the ability to translate requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems Fluent in Korean and English Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco APPLICATIONS CLOSED The general application portal has closed for 2026. We will reopen applications at some point in 2027. Thank you for your interest in Perplexity careers! Welcome! This is the general application portal for university students and recent graduates who wish to be considered for full-time Member of Technical Staff positions at Perplexity. Our elite new grad cohorts enjoy unparalleled mentorship, top-of-market compensation, and the chance to tackle some of the deepest, thorniest challenges in frontier intelligence https://www.perplexity.ai/hub/blog/category/research. NOTE: if you attend one of our focus schools listed below, please do not apply via this portal as it is infrequently monitored due to high volume. Apply instead via the school-specific application portal below to ensure your application receives priority attention. FOCUS SCHOOLS (UNITED STATES) - APPLICATION PORTALS Caltech https://pplx.ai/2026Caltech | Columbia https://pplx.ai/2026Columbia | Cornell https://pplx.ai/2026Cornell | CMU https://pplx.ai/2026CMU | Duke https://pplx.ai/2026Duke | Georgia Tech https://pplx.ai/2026GATech Harvard https://pplx.ai/2026Harvard | MIT https://pplx.ai/2026MIT | Michigan https://pplx.ai/2026Michigan | Northwestern https://pplx.ai/2026Northwestern | NYU https://pplx.ai/2026NYU | Penn https://pplx.ai/2026Penn Princeton https://pplx.ai/2026Princeton | Purdue https://pplx.ai/2026Purdue | Stanford https://pplx.ai/2026Stanford | UC Berkeley https://pplx.ai/2026Berkeley | UChicago https://pplx.ai/2026UChicago UCLA https://pplx.ai/2026UCLA | UIUC https://pplx.ai/2026UIUC | UNC Chapel Hill https://pplx.ai/2026UNC | UT Austin https://pplx.ai/2026UTAustin UWashington https://pplx.ai/2026UW | Yale https://pplx.ai/2026Yale FOCUS SCHOOLS (CANADA) - APPLICATION PORTALS McGill https://pplx.ai/2026McGill | UBC https://pplx.ai/2026UBC | UToronto https://pplx.ai/2026UToronto | Waterloo https://pplx.ai/2026Waterloo EARLY CAREER TALENT @ PERPLEXITY Perplexity believes that exceptionally talented individuals at any stage can thrive in our high-velocity, high-ownership culture. Our early career talent program revolves around: - Breadth: New grads at Perplexity work across the stack, from Perplexity's agent harnesses to our AI inference and training systems. Many of our most beloved features and most important systems were shipped by individuals fresh out of school. - Depth: New grads are entrusted (and expected) to dive deep into whatever problem domains you work on. Often, your work will require you to become a world expert in some problem space that few others in the world have encountered. - Mentorship & Growth: We keep the size of our entering new grad cohorts at well below 10% of our technical team. Each individual enjoys a rich network of mentors to help them grow, and our new grads have a track record of becoming some of Perplexity's most senior and prolific team members. - Recognition: We select for the best and we recognize them accordingly. We set our early career compensation to rise well above that of top tech companies and startups. Post-hire, we aggressively recognize and reward growth in role. - Mission: Perplexity is AI for people who expect more. Our mission is to build frontier intelligence for the world's most discerning users, and each contribution you make will directly advance that mission. ACADEMIC REQUIREMENTS If you're not applying from a focus school listed above, we typically require you to possess the following qualifications: 1. GPA of ≥3.92, averaged across all CS and Math classes; and 2. Grade of A or A+ in your school's upper-level algorithms course. Additional advanced coursework in areas such as systems, AI/ML, advanced math, and other rigorous subjects is highly welcome.   NON-QUALIFYING APPLICATIONS - EVIDENCE OF EXCEPTIONAL ABILITY While you're welcome to submit your application if you don't meet these criteria, we will be looking for other evidence of exceptional ability. You are encouraged to briefly describe this evidence in response to the "Anything Else" question at the bottom of the application form. NOTE ON FELLOWSHIP OPPORTUNITIES This portal accepts applications for full-time roles at Perplexity. Internship applications are not accepted via this portal. If you're interested in short-term opportunities with our team, you may instead be interested in the Perplexity Research Fellowship. The Fellowship has a separate application process detailed here https://pplx.ai/fellowship. Note that Fellowship applications are extremely competitive; in particular, we don't expect to admit any undergraduate students to the Fellowship before their final year of study.

Location: San Francisco APPLICATIONS CLOSED The general application portal has closed for 2026. We will reopen applications at some point in 2027. Thank you for your interest in Perplexity careers! Welcome! This is the general application portal for university students and recent graduates who wish to be considered for full-time Member of Technical Staff positions at Perplexity. Our elite new grad cohorts enjoy unparalleled mentorship, top-of-market compensation, and the chance to tackle some of the deepest, thorniest challenges in frontier intelligence https://www.perplexity.ai/hub/blog/category/research. NOTE: if you attend one of our focus schools listed below, please do not apply via this portal as it is infrequently monitored due to high volume. Apply instead via the school-specific application portal below to ensure your application receives priority attention. FOCUS SCHOOLS (UNITED STATES) - APPLICATION PORTALS Caltech https://pplx.ai/2026Caltech | Columbia https://pplx.ai/2026Columbia | Cornell https://pplx.ai/2026Cornell | CMU https://pplx.ai/2026CMU | Duke https://pplx.ai/2026Duke | Georgia Tech https://pplx.ai/2026GATech Harvard https://pplx.ai/2026Harvard | MIT https://pplx.ai/2026MIT | Michigan https://pplx.ai/2026Michigan | Northwestern https://pplx.ai/2026Northwestern | NYU https://pplx.ai/2026NYU | Penn https://pplx.ai/2026Penn Princeton https://pplx.ai/2026Princeton | Purdue https://pplx.ai/2026Purdue | Stanford https://pplx.ai/2026Stanford | UC Berkeley https://pplx.ai/2026Berkeley | UChicago https://pplx.ai/2026UChicago UCLA https://pplx.ai/2026UCLA | UIUC https://pplx.ai/2026UIUC | UNC Chapel Hill https://pplx.ai/2026UNC | UT Austin https://pplx.ai/2026UTAustin UWashington https://pplx.ai/2026UW | Yale https://pplx.ai/2026Yale FOCUS SCHOOLS (CANADA) - APPLICATION PORTALS McGill https://pplx.ai/2026McGill | UBC https://pplx.ai/2026UBC | UToronto https://pplx.ai/2026UToronto | Waterloo https://pplx.ai/2026Waterloo EARLY CAREER TALENT @ PERPLEXITY Perplexity believes that exceptionally talented individuals at any stage can thrive in our high-velocity, high-ownership culture. Our early career talent program revolves around: - Breadth: New grads at Perplexity work across the stack, from Perplexity's agent harnesses to our AI inference and training systems. Many of our most beloved features and most important systems were shipped by individuals fresh out of school. - Depth: New grads are entrusted (and expected) to dive deep into whatever problem domains you work on. Often, your work will require you to become a world expert in some problem space that few others in the world have encountered. - Mentorship & Growth: We keep the size of our entering new grad cohorts at well below 10% of our technical team. Each individual enjoys a rich network of mentors to help them grow, and our new grads have a track record of becoming some of Perplexity's most senior and prolific team members. - Recognition: We select for the best and we recognize them accordingly. We set our early career compensation to rise well above that of top tech companies and startups. Post-hire, we aggressively recognize and reward growth in role. - Mission: Perplexity is AI for people who expect more. Our mission is to build frontier intelligence for the world's most discerning users, and each contribution you make will directly advance that mission. ACADEMIC REQUIREMENTS If you're not applying from a focus school listed above, we typically require you to possess the following qualifications: 1. GPA of ≥3.92, averaged across all CS and Math classes; and 2. Grade of A or A+ in your school's upper-level algorithms course. Additional advanced coursework in areas such as systems, AI/ML, advanced math, and other rigorous subjects is highly welcome.   NON-QUALIFYING APPLICATIONS - EVIDENCE OF EXCEPTIONAL ABILITY While you're welcome to submit your application if you don't meet these criteria, we will be looking for other evidence of exceptional ability. You are encouraged to briefly describe this evidence in response to the "Anything Else" question at the bottom of the application form. NOTE ON FELLOWSHIP OPPORTUNITIES This portal accepts applications for full-time roles at Perplexity. Internship applications are not accepted via this portal. If you're interested in short-term opportunities with our team, you may instead be interested in the Perplexity Research Fellowship. The Fellowship has a separate application process detailed here https://pplx.ai/fellowship. Note that Fellowship applications are extremely competitive; in particular, we don't expect to admit any undergraduate students to the Fellowship before their final year of study.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Beneficial Deployments Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most. About the Role We're looking for an Applied AI Engineer to join our Beneficial Deployments, Life Sciences team, focused on using Claude to speed up protein and small-molecule design. You'll work with research partners to apply modern design and structure models to real discovery problems, and build the agents and skills that turn those tools into end-to-end workflows. This role is about applying design models, not building new ones. Responsibilities Work with research partners on protein and molecular design end-to-end with Claude, from advising, to prototyping, to writing production code. Work in a design–make–test loop with wet-lab partners (e.g. antibody-repertoire mining, MD prep / trajectory analysis at proteome scale) and turn the expert steps into reusable agents/skills. Build agents and skills that wrap design and structure tools into end-to-end workflows. Support research efforts aimed at better understanding the protein sequence-to-function relationship Help partners measure where AI speeds up their design cycles, and where it doesn't. Drive product, engineering and research direction from field experience, e.g. benchmarks and evals for design and structure tasks (capabilities and safety). Scale your impact to the long tail of labs through reusable skills, cookbooks and docs. Be an ambassador for Claude in molecular design, from small settings to large conferences. You Might Be a Good Fit If You Have Hands-on experience applying protein or small-molecule design to real drug development programs, in an AI-first biotech, pharma, a rare-disease non-profit, a research institute, or a translational academic design lab. Experience with molecular dynamics (system prep, trajectory analysis) or large-scale antibody/immune-repertoire data, and with closing the loop against experimental results from a partner lab. Hands-on use of modern design and structure tools (e.g. AlphaFold, RFdiffusion, ProteinMPNN, Rosetta) to solve design problems, not only to build new models. Strong engineering skills: you can take an LLM-powered tool from prototype to production code, and write evals to measure its performance. Deep understanding on how to quantitatively measure success in drug design, experimentally and computationally. A scientist's instinct for understanding how AI can, and cannot, facilitate protein research and design Experience working directly with external customers or partners in a technical role. Clear written and verbal communication: docs partners can use without you, and talks that earn researchers' trust. A scrappy mentality: comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $280,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Legal Tech engineers play a specialized and critical role in keeping Claude at the frontier. Partnering closely with counsel, we provide custom infrastructure and guidance for complex, novel technical matters, empowering teams across the company to continue meeting our legal obligations as we innovate. As a Senior+ Software Engineer on our Legal Tech team, you'll build dedicated, highly secure, and reliable cloud environments and data processing and storage capabilities at speed and scale. You will own your scope end to end: from raw requirements all the way through to large-scale production systems that satisfy legal invariants and unlock new possibilities. The systems you build won't just be dependable and scalable; they'll be interpretable and auditable, demonstrating to skeptical audiences exactly how they worked and why results can be trusted. You'll be an essential member of a collaborative team, working together to solve difficult problems against fixed deadlines. You will own internal customer relationships as well: you'll gather, prioritize, and coordinate needs from colleagues on Privacy, Security, Research, and/or Infra as well as Legal, to ship the right capabilities on the right timelines. You'll act as a trusted advisor: clearly explaining technical concepts and constraints to inform legal decisions, and proactively designing new approaches to prevent classes of problems. Your infrastructure expertise will directly empower our business to calibrate and manage risk, innovating faster thanks to systems that build in legal considerations. Key responsibilities Build and operate dedicated cloud infrastructure, storage, and data pipelines for specialized workloads that can't run on general-purpose systems Design architectures with excellent security, privacy, reliability, scalability, and auditability baked in Partner with a wide range of internal customer teams to translate requirements into sound approaches and realistic ETAs Deliver against fixed deadlines Support complex and novel legal requests on controlled infrastructure, with verifiable chain of custody Pair with engineering teams across the company to extend existing infrastructure to support new workflows and/or legal requests Work with nontechnical stakeholders to clarify their needs through responsive, easy-to-follow dialogue Minimum qualifications Experience designing, building, and operating highly trusted infrastructure and data systems in production, including owning architectural decisions Experience working across large, complex, multi-team environments, including in stacks and code you don't own Ability to take ownership of a cloud account and secure it end to end (networking, storage, identity, encryption, least-privilege provisioning, etc.) on AWS and/or GCP Ability to translate legal and privacy requirements into sound technical designs and implementations that teams are excited to adopt A habit of verifying rather than assuming: designing checks for invariants and plainly naming what isn't proved Self-directed in a high-change environment, and comfortable resequencing quickly when new needs emerge Clear communication with nontechnical stakeholders, and an understanding of their needs Preferred qualifications Software engineering experience with an infrastructure, data, privacy, and/or security focus Proficiency with large-scale data tooling, such as distributed processing, lakehouse table formats, and/or query engines Understanding of data processing pipelines, LLM training, and/or provenance and lineage Experience with secure enclaves, confidential computing, clean rooms, or other purpose-built environments for sensitive data Background in eDiscovery, litigation support, or records retention at scale, including chain of custody and verifiable integrity The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.