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Location: Bremen, Germany Constructor University in collaboration with Constructor Knowledge Labs and Constructor Technology About the Position The research group of Dr. Sari Sadiya at Constructor Knowledge Labs (CKL) , in collaboration with Constructor University (CU) and Constructor Technology (CT) , invites applicants for Ph.D. student positions in Computer Science with a focus on wearable intelligence, multimodal data fusion, and edge AI . The project investigates how wearable data streams can be transformed into structured knowledge and integrated into a knowledge-grounded digital avatar that supports bi-directional collaboration in education and research. Ph.D. students will work in a highly interdisciplinary environment, combining AI/ML, edge computing, cognitive science, and human–computer interaction . In close collaboration with academia and industry, they will contribute to building privacy-preserving, real-time personalization frameworks while pursuing their doctoral dissertation. About the Program The PhD program is research-centered, emphasizing original contributions in: Wearable data analytics and fusion methods Biomedical data analytics On-device processing and performance modeling Personalization and adaptive reasoning systems AI for Education Doctoral students will also have access to specialized courses in: Artificial Intelligence, Machine Learning, and Edge Computing Advanced Computational Methods and Data Science Cognitive Science and Human-Centered Computing As part of the program, students will collaborate with Constructor Technology to gain first-hand industrial experience, contributing to real-world testbeds and prototypes. Research Focus This PhD position is part of the Wearable Intelligence Project , with two main research directions: Data fusion of heterogeneous temporal streams Designing algorithms to unify multimodal signals (physiological, cognitive, contextual, scheduling, and learning data). Developing pipelines that produce structured insights powering the Agentic Personalization Engine (APE) . On-device data processing & performance modeling Developing models balancing computation, energy, and data flows across wearable, edge, and cloud environments. Exploring feasibility of running compact micro-LLMs directly on wearables . The overarching goal is to create scalable, ethical, and transparent personalization systems that support education and research. Funding The appointment provides full financial coverage through a dedicated fellowship, comprising: Monthly stipend of €1,650 Monthly research-cost allowance of €100 (Forschungskostenpauschale) Health-insurance subsidy of €100 per month Supplementary €603 mini-job allowance to support parallel part-time employment (optional) Constructor Knowledge Labs actively supports candidates in preparing applications for external funding — doctoral scholarships, foundations, or international mobility grants — and can provide institutional support and references Applicant Profile Mandatory requirements: MSc degree (or equivalent) in Computer Science, AI/ML, Data Science, Cognitive Science, or related disciplines. Strong background in AI/ML, signal processing, or edge computing. Hands-on experience with wearable or multimodal data (e.g., heart rate, EEG, activity, sleep, GPS) . Solid mathematical and computational modeling skills. Proficiency in academic English writing (e.g., reports, papers, theses). Preferred qualifications: Experience with LLMs, multimodal data fusion, or agent-based AI systems . Familiarity with privacy-preserving ML, dynamic consent, and GDPR-compliant frameworks . Demonstrated ability to conduct independent research and collaborate across disciplines. Interest in teaching, mentoring, and applied industrial research. Application Details Deadline : August 31, 2026 Required documents: Curriculum Vitae (CV); Academic transcripts; Letter of motivation outlining research interests and career goals; 2 recommendation letters. Applications to be reviewed on a rolling basis. Shortlisted candidates will be invited to interviews.

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 team Anthropic's Life Sciences team is building a world-class research group focused on making fundamental biological discoveries. The team combines cutting-edge AI with hands-on biological research, positioning Anthropic at the forefront of AI-accelerated scientific discovery. About the role We're seeking an exceptional Research Scientist to join the team. This role combines deep computational biology expertise with frontier AI capabilities, positioning Anthropic at the forefront of AI-driven scientific discovery. As one of the first computational members of this Life Sciences research group, you'll work on a high-impact team that operates at the intersection of computational and experimental biology. You'll bring broad computational biology experience to bear across the team's projects, driving discoveries from large-scale computational analysis of biological data through to results our experimental scientists can test, and moving flexibly between problems as the science demands. You'll have substantial access to Claude and you'll help establish how computational biology operates at Anthropic. This role offers a unique opportunity to shape how AI transforms biological research. You'll work with some of the world's best AI researchers while tackling problems that matter deeply for scientific understanding and biomedicine. If you're excited about using your computational expertise to make fundamental biological discoveries and guide the development of transformative AI systems, we want to hear from you. Key responsibilities Build, run, and maintain the analysis pipelines that back the team's experimental programs: sequence analysis at petabyte scale, structural bioinformatics, phylogenetic and comparative genomics, design and analysis of high-throughput functional screens, biological sequence modeling, etc. Partner directly with experimental biologists to design experiments that produce high-quality data, and turn results around fast enough to immediately inform the next experiment Draw on the literature and curated biological knowledge bases alongside primary data to generate and prioritize hypotheses for experimental follow-up Stand up and maintain the team's computational infrastructure: data ingestion, workflow orchestration, internal databases, and the interfaces that make all of it accessible to both researchers and AI agents Use Claude and our internal agent frameworks heavily in your own work, and feed what you learn back to the model-improvement and product teams as evaluations, datasets, and concrete failure cases Pick up analyses across projects as priorities shift; we're looking for breadth and flexibility over a single deep specialty Minimum qualifications Have a PhD in computational biology, bioinformatics, genomics, biophysics, machine learning, computer science, or a related quantitative or biological field, or equivalent industry research experience Have a track record of computational biology research you have led end to end, from question to result, with evidence of impact (for example publications, preprints, released datasets or tools, or research that changed a program's direction) Have demonstrated breadth across multiple areas of computational biology Are proficient in one or more programming languages used in scientific computing and comfortable working on large datasets in Linux and cloud compute environments Can take an ambiguous biological question, scope the analysis, and produce a result an experimentalist can act on Communicate computational results clearly to both biologists and ML researchers Preferred qualifications Are comfortable navigating ambiguity and developing solutions in rapidly evolving research environments Are results-oriented, with a bias towards flexibility and impact Hands-on experience in experimental biology, or a track record of designing experiments side by side with experimentalists Experience building tools, pipelines, or agentic systems on top of LLMs, or training models on biological sequence data Deep expertise in one or two areas of computational biology (for example structural biology, metagenomics, single-cell genomics, or protein design) on top of the required breadth 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: $300,000 — $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: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. OUR MISSION At Humanoid we strive to create the world's leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into daily life and amplify human capacity. ABOUT THE ROLE As a Research Engineer on the World Models team, you will build action-conditioned generative models that predict how the world evolves around our robots — future video, proprioception, contacts, and outcomes — from past observations and actions. World models serve four purposes in our stack: a pretrained, physics-aware prior for our VLA policies; an engine for rare data collection, cross-platform transfer, and sim-to-real transfer; a testbed for policy evaluation and testing before hardware; and a future-prediction rollout engine that surfaces what our policies intend to do, for safety and planning. This is a hands-on individual contributor role: you will design architectures, run large training jobs, and validate your models against real fleet data from industrial deployments. WHAT YOU'LL DO - Design and train multimodal world models — video, state, action, and language — using diffusion-based and transformer architectures. - Build action-conditioned video prediction and dynamics models that stay physically consistent over long horizons, including contact-rich manipulation, and serve as pretrained priors for VLA policies. - Develop learned-simulator evaluation: score candidate policies offline, predict real-world success rates before deployment, and roll out policy futures to expose intended behaviour for safety review and planning. - Generate synthetic rollouts and counterfactual experience — including rare events, cross-platform transfer, and sim-to-real transfer — to augment policy training, and measure their effect on downstream task performance. - Establish fidelity metrics and calibration protocols that quantify where the world model can be trusted and where it diverges from reality. - Build data pipelines that turn fleet telemetry, teleoperation logs, and internet-scale video into training corpora for world models. - Run scaling and ablation studies on architecture, data mixture, and context length; communicate findings crisply. - Collaborate with pretraining, RL, and manipulation teams to integrate world models into policy training and evaluation loops. WHAT WE'RE LOOKING FOR - A track record of training large generative models — video, world, or multimodal — with shipped models or published artifacts to show for it. - Deep hands-on experience with modern generative architectures: diffusion models, autoregressive transformers, latent-variable models, or video prediction. - Experience with large-scale distributed training: streaming datasets, checkpointing and state management, debugging numerics and training instabilities. - Strong Python + PyTorch/JAX; you can profile kernels, optimize data loaders, and write maintainable research code. - Empirical rigor: you design careful evaluations, run honest baselines, and document experiments clearly. - Excitement about grounding generative models in physical reality rather than pixels alone. NICE TO HAVE - Experience with world models for robotics or autonomous driving (e.g., action-conditioned video models, learned simulators, model-based RL). - Familiarity with robotics simulators (Isaac Sim, MuJoCo) and sim-to-real considerations. - Experience using world models for policy evaluation or synthetic data generation at scale. - Publications at top-tier deep learning conferences (NeurIPS, ICML, ICLR, CoRL, CVPR) or equivalent open-source contributions. - Experience optimizing generative models for fast inference. WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Location: San Francisco, CA | Washington, DC 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 hiring a Field Marketing Lead dedicated to the Public Sector Industry — one of the fastest-growing customer segments we serve, and one we believe will define how the next generation of AI-native companies adopts and builds with Claude. You will own the field marketing strategy and end-to-end execution for Public Sector audiences in the US, partnering closely with our Public Sector Sales teams. This is a builder role. Field Marketing at Anthropic is a small, scrappy team and the Public Sector is an area of growth for the business — there is no existing playbook for you to inherit. You will design the event calendar, build the integrated digital programs, develop the necessary partnerships, and create the playbooks that scale across our Public Sector motion. Responsibilities Develop and activate the US Public Sector field marketing strategy end-to-end — planning, calendar, execution, and measurement. Design and run public-sector-appropriate event formats — agency roundtables, mission-focused briefings, tech demo days, industry days, and executive breakfasts — that comply with government ethics and gift rules while building trusted relationships with program and procurement stakeholders Plan the field calendar around the government fiscal year — building demand programs that peak ahead of federal year-end (September 30) and state budget cycles, and capitalize on use-it-or-lose-it spending windows Own presence at anchor public sector events — from sponsorship strategy to speaker placement and on-site execution Build co-marketing programs with the public sector channel ecosystem — distributors, resellers, systems integrators, and contract-vehicle holders — including joint events, teaming-oriented content, and partner-sourced pipeline Partner closely with Public Sector Sales and BDRs on pre-event targeting, during-event engagement, and post-event follow-up to convert attention into pipeline Build operational playbooks (Demo Day activation kit, hackathon kit) that the Field Marketing team can scale across regions and segments Establish baseline metrics, dashboards, and ROI reporting for all Public Sector field programs Be the face of Anthropic in the Public Sector ecosystem — credible with strategic partners and agencies Minimum qualifications Direct Public Sector-segment experience — you have built and run programs targeting the Public Sector as your primary audience, not as an enterprise field marketer who occasionally touches Public Sector End-to-end ownership of field marketing events and programs, hands on in both strategy and execution - this is a 0-1 building role with very little foundation in place Repeat success across multiple companies — we are looking for a pattern of impact, scaling field or demand generation programs in different environments, not a single-company tour (however strong the brand) 0-to-1 builder DNA — you've built a field marketing motion from scratch (or rebuilt one), and you also have scaled-company tenure that grounds you operationally Tight sales alignment — you've worked shoulder-to-shoulder with AEs and BDRs on account targeting, pre-event outreach, and post-event follow-up Operational rigor — you can stand up vendor management, registration, follow-up workflows, and ROI dashboards without being asked Technical credibility — you can review technical event content, brief technical speakers, and hold your own with founder/CTO audiences Preferred qualifications 10+ years across Field Marketing, Demand Generation, ABM, and Events at B2B technology companies Experience working inside of a Public Sector organization that went through a rapid growth phase, or a blend of Public Sectors and scaled technology companies. AI/ML field marketing experience Existing relationships with public sector associations and research institutions Visible thought leadership in the Public Sector ecosystem or developer ecosystem Role-specific policy: For this role, we expect staff to be able to work from our San Francisco or Washington, D.C. office at least 2 days a week. We encourage you to apply even if you might need some flexibility for an interim period of time for relocation. 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 — $400,000 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, United States 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 Anthropic Anthropic's mission is the responsible development and maintenance of advanced AI for the long-term benefit of humanity. We are a safety-focused AI company working to build reliable, interpretable, and steerable AI systems. As our compute infrastructure scales to support frontier model training and deployment, we are building a world-class team to design, deliver, and operate the physical facilities that make that possible. About the Role We are looking for a Principal Data Center Architect with deep expertise in Civil, Structural, and Architectural (CSA) design to join our growing infrastructure team. This role is the technical owner for the physical building fabric of Anthropic's AI compute facilities — from the earliest site feasibility studies and test fits through reference design development, design partner oversight, and construction delivery. As Anthropic scales its data center program across multiple sites in the United States and internationally, you will set the civil, structural, and architectural standards that govern how our facilities are designed and built. You will work directly with design-build partners, AE firms, and internal mechanical, electrical, and IT infrastructure teams to ensure our facilities are optimized for high-density AI workloads, constructable on aggressive timelines, and replicable across a growing portfolio. This is an owner's engineer role — you are the technical authority, not a consultant. You will be expected to make binding design decisions, identify problems before they reach the field, and drive standardization across a pipeline of concurrent projects globally. What You'll Do Own the civil, structural, and architectural reference design standards for Anthropic's data center portfolio, establishing repeatable design elements deployable across multiple sites and jurisdictions Lead front-end test fits and site feasibility studies, evaluating structural approaches, site constraints, utility interfaces, and code compliance to inform site selection and design direction Review and approve CSA deliverables from design-build partners and AE firms at each design stage (SD, DD, CD, IFC), including drawings, structural calculations, specifications, and geotechnical reports Integrate CSA design with mechanical, electrical, plumbing, fire protection, and IT infrastructure teams to produce coordinated designs that support high-density AI compute and direct liquid-cooling systems Drive site and campus planning to maximize compute density, optimize construction phasing, and align physical layout with IT and operational requirements Partner with the construction and delivery team to provide technical oversight during construction, resolve field issues, and support commissioning activities Evaluate and develop relationships with design partners, structural engineering subconsultants, and prefabrication / modular vendors; define qualification and performance standards Establish and maintain facility support area standards — logistics staging, loading, maintenance access, and operational support spaces — scaled for hyperscale deployments Identify modular and prefabricated construction opportunities that reduce schedule, cost, and design risk across the project pipeline Manage review cycles and coordinate across internal and external stakeholders to resolve design conflicts and keep projects moving on aggressive timelines Travel to project sites globally for design reviews, construction audits, and commissioning milestones (up to 40%) What We're Looking For Required 10+ years delivering mission-critical facility infrastructure, with at least 6 years directly in hyperscale or large-scale data center CSA design Deep technical expertise across civil site development, structural design, and architectural programming for industrial or mission-critical facilities Demonstrated experience as an owner's engineer or lead technical authority — setting standards, approving deliverables, and managing external design teams Proficiency with applicable building codes and standards including IBC, IFC, ASCE 7, ACI 318, AISC, FM Global, and local jurisdictional requirements across multiple geographies Experience with high-density compute environments, including structural and architectural accommodation of direct liquid-cooling systems, overhead busway, and dense rack deployments Track record of driving design standardization and developing repeatable reference designs across a multi-site portfolio Ability to evaluate and red-line structural calculations, civil site plans, and architectural construction documents for accuracy, completeness, and constructability Experience coordinating across MEP disciplines and IT infrastructure teams in a fast-paced, multi-project environment Clear and direct communication with both technical and non-technical audiences; ability to make and defend design decisions with incomplete information Preferred Licensed Professional Engineer (PE) in civil or structural engineering, or licensed architect (AIA / RA) Experience with prefabricated and modular construction strategies for data center applications Familiarity with geotechnical risk assessment and foundation design for large industrial facilities LEED accreditation, Uptime Institute AOS/M&O certification, or equivalent mission-critical credentials International project delivery experience (Europe, Asia-Pacific, or other regions) Experience reviewing design packages in Autodesk Construction Cloud, Revit, or Navisworks 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: 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 As a Technical Recruiter at Anthropic, you will be instrumental in shaping the future of our organization by identifying, engaging, and hiring the best and brightest minds across a range of disciplines. As we continue to push the boundaries of AI research and development, we need a passionate recruiter who can help us build a world-class team dedicated to creating safe and beneficial AI systems. Key Responsibilities Develop and execute strategic recruiting plans to identify and source highly qualified candidates Partner with technical and non-technical hiring managers and interviewers to understand hiring needs, team matching, required skills and qualifications Implement recruiting processes and programs such as developing targeted outreach campaigns, building connections with industry leaders, and removing any unfair biases from the hiring process Collaborate with leadership and cross-functional partners to understand organizational needs and map out long-term talent acquisition strategies that balance priorities across all technical teams Enhance Anthropic’s employer brand to showcase our mission, culture, and values to candidates Provide an exceptional candidate experience throughout the recruiting process Minimum qualifications Deep full lifecycle recruiting experience, with substantial time supporting technical engineering organizations Proficiency with an applicant tracking system like Greenhouse and other modern sourcing tools Experience partnering directly with hiring managers on intake, bar calibration, and interview loop design Sound independent judgment on candidate quality, and the ability to independently partner with multiple hiring managers are complex searches Genuine interest in Anthropic's mission and in the role a strong security function plays in achieving it Preferred qualifications Experience recruiting at a high-growth technology, AI, or machine learning company Working knowledge of the security credential landscape and clear judgment about where those credentials carry signal and where they do not Experience hiring for engineering, incident response, threat intelligence, insider risk, or physical security Experience improving recruiting processes, market maps, or interview architecture where they were thin or absent Comfort using LLMs to accelerate sourcing, research, and market mapping 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: $240,000 — $295,000 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 Anthropic manages one of the industry's largest AI fleets — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around Capacity. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Directly influence decisions around a significant area of company investment. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at very large scale. 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.

Location: San Francisco, CA | New York City, NY | Washington, DC 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 Safeguards Enforcement Analyst on the account abuse team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your initial focus will be account compromise: Anthropic's enforcement systems have to distinguish customers whose accounts have been compromised from actors abusing the platform — and today those two populations can look identical in the data. Stolen credentials and leaked keys are a growing abuse vector, and the collateral damage from enforcement against them lands on legitimate users. You'll own this problem end to end: detection, revocation, user notification, remediation, and the criteria for restoring access — turning what is today ad hoc incident response into a scalable, repeatable program. This position may expand into broader areas of enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way. Key responsibilities Investigate credential-compromise incidents across first-party and third-party platforms, tracing actor behavior across accounts and surfaces Design and operate remediation workflows for compromised accounts: revocation, customer notification, and standards for restoring access Partner with Engineering and Data Science teams to improve how we separate compromised-customer traffic from willful abuse Enforce usage policies with a focus on detecting and mitigating potentially harmful use of AI systems Work with threat intelligence on emerging credential-abuse patterns and the actors behind them Support the Safeguards policy design team by providing detailed feedback on policy gaps based on real enforcement scenarios Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows Write the policy framework for compromise scenarios, including cases where Anthropic can't independently verify a customer's security posture Act as the enforcement SME when account compromise intersects with active abuse investigations Minimum qualifications Experience in trust and safety, fraud investigation, security operations, or a related field Subject matter expertise in one or more of: account takeover, credential abuse, session security, or incident response Experience designing or operating enforcement, remediation, or customer-recovery flows — not just detection Comfort using data (SQL or similar tools) to trace actor behavior across accounts and to measure what's working A thoughtful perspective on the tension between protecting the platform and restoring access for legitimate compromised customers Strong written communication skills, with experience producing clear briefs about messy incidents for technical and non-technical stakeholders Excellent judgment and the ability to collaborate with team members while navigating rapidly evolving priorities and workstreams Preferred qualifications Familiarity with credential-theft ecosystems or threat intelligence tooling Experience working with fraud/risk vendors (e.g., device or network intelligence platforms) Experience with API platform abuse specifically, not just consumer-account ATO A deep interest in AI safety and responsible technology development Experience writing effective prompts for generative AI systems in a content review or enforcement context 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: $245,000 — $285,000 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 | Washington, DC 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 Safeguards Enforcement Analyst on the account abuse team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your focus will be driving a number of enforcement areas including access controls and identity verification. You'll own the policy layer of these systems: what we ask users for, when, on what grounds, and what passes. The work sits at the intersection of policy, operations, and regulatory exposure. This position may expand into broader areas of enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way. Key responsibilities Set collection policy for identity signals: what we request, in which enforcement states, and what evidence reinstates access Improve verification program health — accuracy, appeal coverage, and consistency of outcomes Own access policy for hard cases, including geographic restrictions and reseller arrangements Run the operational queue for access-control cases alongside contractor support, authoring playbooks and QA'ing scaled review output Work with Legal, Public Policy, and Privacy stakeholders to keep our approach proportionate, privacy-preserving, and responsive to an evolving regulatory landscape Coordinate enforcement consistency with third-party platform partners Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows Stand up graduated enforcement in practice — verification requests, conditional reinstatement, and appeal pathways that satisfy regulatory requirements for automated decisions Minimum qualifications Experience in trust & safety, integrity, or risk policy work Hands-on operational experience — you've owned or quality-checked live enforcement queues, not only authored policy Subject matter expertise in one or more of: KYC, identity verification, age or identity assurance, or verification program operations Experience navigating evolving regulatory landscapes (including frameworks like the DSA and GDPR) as design constraints rather than blockers Experience driving cross-functional initiatives with Product, Engineering, Legal, and Policy partners — especially where safety, privacy, and usability tradeoffs need to be navigated together Comfort using data (SQL or similar tools) to measure what's working and inform decisions Strong written communication skills, with experience producing clear briefs and recommendations for technical and non-technical stakeholders Excellent judgment and the ability to make consistent, defensible calls on ambiguous cases Preferred qualifications Experience with graduated/tiered enforcement systems rather than binary ban models Experience with geographic access restrictions, sanctions screening, or reseller/channel policy Experience building or scaling a contractor review bench A deep interest in AI safety and responsible technology development Experience writing effective prompts for generative AI systems in a content review or enforcement context 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: $285,000 — $330,000 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: New York City, NY; 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 The Safeguards team is responsible for ensuring our models and products are developed and deployed safely. We're looking for engineers for our Review Tooling team, which builds the systems that humans — and increasingly Claude — use to investigate potential harms and take enforcement actions across Anthropic's first-party products and third-party cloud platforms. You'll own the tools our safety investigators rely on to understand what's happening on our platforms and act on it, as well as the platform underneath those tools. That platform includes data analysis capabilities, privacy-preserving primitives that keep review workflows compatible with our data retention commitments, and a sandbox environment where new review interfaces and workflows can be built and iterated quickly. These are internal tools, but they are anything but low-stakes: the speed, clarity, and reliability of this tooling directly determines how quickly Anthropic can identify harmful behavior, make sound enforcement decisions, and feed signals back into model training and safety classifiers. You'll partner closely with policy, operations, data science, legal, and privacy teams to ensure our enforcement systems are effective, accurate, and trustworthy. Key responsibilities Build investigation, review, and enforcement tooling for both first-party and third-party platform surfaces — including case queues, investigation views, decision and audit logging, and account-actioning workflows Develop the platform layer of reusable APIs, data storage, and backend services that lets new review workflows be stood up quickly and safely Stand up and run deployments of this tooling across multiple clouds, including inside cloud-provider partner environments where data must stay in place. Keep the deployments consistent through shared deployment pipelines, smoke tests, observability, and alerting Scale review through automation, including enabling reviewers to use Claude effectively and building toward Claude-assisted and Claude-driven review workflows Partner with policy, operations, legal, privacy, and data science stakeholders to translate enforcement and investigation needs into reliable, well-designed systems that measurably reduce handling time and decision error Instrument the tools you ship — surfacing metrics on queue health, reviewer throughput, and decision quality — and ensure tooling evolves alongside new privacy primitives and data retention commitments Minimum qualifications A technical background in full-stack or platform engineering, with the ability to engage deeply in architecture and design discussions Experience shipping internal tools or platforms with demanding operational users, and a track record of improving their workflows measurably Experience working cross-functionally with non-engineering partners such as operations, policy, or legal teams Excellent communication skills, including the ability to explain technical tradeoffs to non-technical stakeholders Care about the societal impacts of AI and want your work to make powerful systems safer Preferred qualifications 8+ years of industry software engineering experience Experience building data labeling, trust and safety, integrity, fraud, or abuse-prevention tooling, or other systems supporting human review at scale Have built systems that handle sensitive or regulated data, with requirements around access control, auditability, retention, and data residency Have worked across multiple cloud providers, or built infrastructure designed to be provider-agnostic A product-minded approach to internal users: you work directly with the people using your tools, watch where they struggle, and fix it 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.

Location: Sahibzada Ajit Singh Nagar (Mohali), India Workplace: hybrid We are currently seeking an Applied Machine Learning / Computer Vision Engineer to join one of our clients’ innovative AI teams. This is an exciting opportunity to work on a next-generation AI platform combining Computer Vision, Multimodal AI, Applied Machine Learning, and Large Language Models . Key Responsibilities As an Applied ML / Computer Vision Engineer, you will: Design, develop, and improve Computer Vision and image-processing pipelines. Build solutions for video analysis, video understanding, and real-time visual processing. Develop multimodal AI systems combining vision, audio, and language data. Work with object detection, image segmentation, classification, tracking, and related Computer Vision techniques. Implement and fine-tune Vision-Language Models and Transformer-based architectures. Integrate Large Language Models into AI products for reasoning, analysis, and automated decision-making. Evaluate, optimize, and deploy machine-learning models in production environments. Improve model inference speed, accuracy, scalability, and resource efficiency. Translate research papers and emerging AI techniques into practical product features. Build APIs and production-grade services for AI model integration. Collaborate with engineering and product teams to understand business requirements and deliver effective AI solutions. Monitor model performance and continuously improve deployed systems. Maintain clear, reusable, and well-documented code. 1–4 years of experienc e in Applied Machine Learning, Computer Vision, Deep Learning, or a related field. Strong programming skills in Python. Hands-on experience with PyTorch. Practical knowledge of OpenCV and image or video processing. Strong understanding of Deep Learning fundamentals. Experience with object detection and/or image segmentation models. Knowledge of Transformer architectures. Experience working with Vision-Language Models. Familiarity with the Hugging Face ecosystem. Experience with model inference, evaluation, and optimization. Understanding of how to move models from experimentation into production. Experience using Docker and Git . Ability to independently investigate technical challenges and propose practical solutions. Ability to understand, reproduce, and implement methods described in research papers. Strong analytical and problem-solving skills. Curiosity and willingness to explore new technologies. Passion for AI, Machine Learning, and product development. Ownership mindset and accountability for delivered solutions. Ability to work independently and contribute within a collaborative team. Interest in building practical products rather than focusing only on model experimentation. Comfortable working in a fast-moving and research-driven environment. Nice to Have Experience with one or more of the following technologies would be considered an advantage: YOLO GroundingDINO SAM or SAM2 Florence-2 Whisper Qwen2.5-VL LLaVA InternVL CUDA TensorRT ONNX FastAPI (Exceptional fresh graduates may also be considered if they can demonstrate strong technical knowledge through relevant academic work, personal projects, GitHub repositories, Kaggle participation, research, or a technical portfolio.)

Location: San Francisco, CA | New York City, NY | Washington, DC 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 an Enforcement Analyst focused on Bio Harms, you will play a critical role in protecting against the misuse of AI systems for biological and related CBRNE harms. You will enforce our Usage Policy with a specific focus on detecting and mitigating bio risks, investigating potential violations, and help continuously strengthen our safeguards.  The work sits at the intersection of biosecurity threat analysis and platform enforcement: you will read real model interactions and make fast, well-reasoned calls about whether activity is benign research or a credible attempt at harm. This role is a fit for someone who understands the dual-use nature of biology and enabling technologies well enough to separate the benign from the malicious. You will own and continuously improve the enforcement monitoring workflows for the bio-harms area, and you will work closely with Policy, Threat Intelligence, Data Science, and Engineering cross-functional partners to accomplish tasks at scale. Safety is core to our mission, and your work will directly protect individuals, communities, and critical systems. Important context for the role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including material of a sexual, violent, or psychologically disturbing nature. The role also carries a shared on-call responsibility across the Policy and Enforcement teams. Key responsibilities Enforce Usage Policies with a specific focus on detecting and mitigating potential bio risks and harmful use of AI systems. Take ownership of enforcement monitoring workflows for the bio-harms area, improving end-to-end detection, investigation, triage, and escalation processes. Monitor and analyze platform activity to identify emerging patterns related to biological (and adjacent chemical, radiological, nuclear, and explosive) threats that may require policy updates or enforcement action. Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy across a technically complex content surface. Conduct thorough investigations of potential violations, gathering and documenting evidence to support enforcement decisions. Proactively surface trends and propose improvements to detection methods and review workflows. Partner with Engineering and Data Science teams to optimize detection models and automated enforcement systems for bio-related policy violations. Partner with Policy and Threat Intelligence groups to understand potential exploits and contribute to risk-assessment frameworks, and partner with engineers iterating on safety systems. Provide enforcement-grounded feedback on policy gaps, and handle escalations and time-sensitive situations related to potential bio-related Usage Policy violations. Minimum qualifications Hold a degree in a bio-related field (e.g., microbiology, molecular biology, biochemistry, public health) and/or relevant professional experience in a related field. Possess experience in Trust & Safety, content moderation, or policy enforcement at platform scale, including working with generative AI tools to refine and optimize content review and enforcement workflows. Possess experience in utilizing AI tools to develop data dashboards for metrics collection in support of continuous improvement efforts. Can analyze complex, ambiguous situations and make well-reasoned, defensible decisions under time pressure. Are proactive and self-directed: you spot trends, dig in, and ship improvements on your own initiative. Communicate clearly in writing and can translate technical bio concepts for diverse audiences, including both technical and non-technical stakeholders. Preferred qualifications Subject matter expertise in biodefense, biosecurity, WMD/CBRNE non-proliferation, or threat-intelligence. An understanding of where real-world biological risk actually lies — adversary intent, acquisition and weaponization pathways, and dual-use concerns, including familiarity with cross-platform threat analysis and open-source intelligence (OSINT) techniques relevant to weapons of mass destruction. Proficiency in SQL and/or other data analysis tools to draw insights from large datasets and monitor enforcement workflow health. Familiarity with dual-use research of concern (DURC), select agents, and relevant policy frameworks. 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: $245,000 — $285,000 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 The Claude Platform ships fast, and every launch lands better when the field can understand it, demo it, and teach it. You'll own platform enablement end to end: the demos, hands-on labs, and technical curriculum that let Anthropic's go-to-market teams showcase the Claude Developer Platform with confidence, whether they're building on Anthropic's first-party API or through Bedrock, Vertex, and Foundry. You'll join roadmap and launch planning with the product team before features ship, so the field has what it needs on day one. You're an engineer who teaches. You've shipped products to users. You know the difference between a demo that raises awareness and one that creates champions. And you get as much energy from watching a seller nail your lab as from building it yourself. Key responsibilities Turn launches into field-ready content: Translate new platform capabilities (API, tool use and MCP, Agent SDK, memory and skills) into demos, labs, and quick-reference guides within days of release, and build compelling demo scenarios across industries and developer personas Deliver training that sticks: Run Claude Platform training for technical onboarding and ongoing enablement programs, delivering hands-on sessions wherever the field gathers, from a 12-person lab to a 100-person field-readiness day Coach the field: Coach technical sellers on demo delivery through practice sessions and office hours Scale beyond the live session: Develop self-service resources and experimental tools so the field can learn without you in the room, and contribute to the tooling that scales enablement, including demo environments, content-freshness automation, and self-service infrastructure Close the loop with product: Stress-test new platform features before launch, then bring field signal back to product and product marketing on where sellers get stuck and what content would unlock the next deal Measure what lands: Track content usage and session feedback so you know what is working and what to retire Minimum requirements Experience in a customer-facing technical role, such as solutions architecture, sales engineering, developer relations, or technical enablement Experience writing production-quality code and building technical demos Hands-on experience building with LLM APIs and agents, including tool use, MCP, or agent frameworks, beyond prompting alone Experience using AI coding tools as part of your daily engineering work Experience delivering live technical training or talks to both technical and non-technical audiences Experience partnering directly with sales, solutions engineering, or other go-to-market teams Preferred requirements A portfolio you can show us: labs, courses, talks, or repos you built yourself Experience with Claude Code, or a comparable agentic coding tool, as core infrastructure in your daily work Experience building on the Claude Developer Platform through cloud providers such as Amazon Bedrock, Google Vertex AI, or Microsoft Foundry Experience as a technical founder, early startup employee, or 0-to-1 operator who has taken an idea to product-market fit Public speaking, conference presentations, or community-facing developer advocacy Experience building enablement tooling, such as demo environments, content-freshness automation, or self-service infrastructure Deep enthusiasm for AI and genuine care about building it responsibly 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: $290,000 — $365,000 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 | Washington, DC 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 Safeguards Analyst focusing on Integrity & Authenticity, you will be responsible for building and executing enforcement workflows for our products and services, with a focus on detecting and mitigating attempts to misuse Anthropic's AI systems for coordinated inauthentic behavior, election manipulation, and targeting, tracking, and surveillance of individuals. Your work will span a broad and interconnected set of harm areas: AI-enabled influence operations and disinformation campaigns, the abuse of AI to interfere with electoral processes, and the use of AI systems to facilitate stalking, surveillance, profiling, and the targeting of individuals or groups. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way. Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a political, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays, particularly around major electoral events. Key responsibilities Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy Partner with Engineering and Data Science teams to optimize detection models for policy violations and automated enforcement systems Review flagged content to drive enforcement and policy improvements Enforce usage policies with a focus on detecting and mitigating AI-enabled influence operations, coordinated inauthentic behavior, election interference, and targeting, tracking, or surveillance of individuals and groups Support the Safeguards policy design team by providing detailed feedback on policy gaps based on real enforcement scenarios Keep up to date with emerging AI policy enforcement best practices, evolving threat actor tactics, and the regulatory landscape around elections, privacy, and surveillance, using these to inform our decision-making and workflows Minimum qualifications Experience in trust & safety, policy enforcement, threat intelligence, or a closely related field with a focus on one or more of: influence operations, disinformation, coordinated inauthentic behavior, election integrity, or privacy and surveillance harms Experience standing up and scaling policy enforcement or content review workflows Proficiency in SQL and/or other data analysis tools to draw insights from large datasets Experience identifying emerging risks and threat actors, and communicating findings to a diverse set of stakeholders, such as Product, Policy, Engineering, and Legal teams Experience working with generative AI products, including writing effective prompts for content review and enforcement Understanding of the challenges involved in implementing product policies at scale, including in the content moderation space Preferred qualifications Experience conducting cross-platform investigations into influence operations, coordinated inauthentic behavior, or disinformation campaigns Familiarity with open-source intelligence (OSINT) techniques and tools used for threat actor tracking and network analysis Working knowledge of privacy law, surveillance technology, or data broker ecosystems as they relate to targeting and tracking harms Experience with large language models and an understanding of how AI technology could be misused to generate synthetic personas, fabricate quotes, or automate persuasion at scale Familiarity with election security frameworks, campaign finance law, or electoral integrity standards in one or more jurisdictions Experience navigating evolving regulatory landscapes relevant to this space (e.g., DSA, EU AI Act, FEC regulations, GDPR) Experience working with election bodies, civil society organizations, or government agencies on integrity or disinformation-related issues Proficiency in Python for data analysis and automation Experience with dark web monitoring or tracking threat actors across surface, deep, and dark web environments 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: $285,000 — $330,000 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 Anthropic's Safeguards team is seeking a Red Team Engineer to help ensure the safety of our deployed AI systems and products. In this role, you'll take an adversarial approach to uncover vulnerabilities across our product ecosystem before they can be exploited by malicious actors. Your work will span from technical infrastructure vulnerabilities on our products to emergent risks from advanced AI capabilities. While you'll bring best practices from traditional security approaches, the focus is on broader safety implications and novel abuse unique to advanced AI systems and associated products. You'll investigate the full spectrum of potential abuse — from coordinated account manipulation and payment fraud to novel exploitation of product features — and simulate sophisticated threat actors who chain multiple attack vectors to achieve their objectives. Key responsibilities Conduct comprehensive adversarial testing across Anthropic's product surfaces, developing creative attack scenarios that combine multiple exploitation techniques Research and implement novel testing approaches for emerging capabilities, including agent systems, tool use, and new interaction paradigms Design and execute "full kill chain" attacks that emulate real-world threat actors attempting to achieve specific malicious objectives Build and maintain systematic testing methodologies that evaluate every aspect of our systems Develop automated testing frameworks to enable continuous assessment at scale Collaborate with Product, Engineering, and Policy teams to translate findings into concrete improvements Help establish metrics for measuring detection effectiveness of novel abuse Minimum qualifications Experience in penetration testing, red teaming, or application security Experience in model jailbreaking and testing large-scale agentic workflows for non-obvious prompt injection vectors Strong technical skills in web application security, including hands-on expertise with security testing tools (e.g., Burp Suite, Metasploit, custom scripting frameworks) Experience building custom automation, including LLM-specific testing frameworks A track record of discovering novel attack vectors and chaining vulnerabilities in creative ways A public body of work such as CVEs, blog posts, or disclosed bug bounty reports Strong written and verbal communication skills, with the ability to explain technical concepts to varied audiences Preferred qualifications Experience with AI/ML security or adversarial machine learning Understanding of AI safety considerations beyond traditional security, including modern guardrails against jailbreaks Experience testing API security and rate-limiting systems Background in testing business logic vulnerabilities and authorization bypass techniques Background in anti-fraud, trust & safety, or abuse prevention systems Familiarity with distributed systems and infrastructure security Familiarity with abuse detection mechanisms and the ability to engineer novel bypasses Adaptability to understand and build engagements around emerging threats outside your direct area of expertise 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: Paris; London Workplace: OnSite ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role As an AI Scientist, you will push the boundaries of AI by developing and scaling cutting-edge models. This role exists to advance Mistral’s mission of democratizing frontier intelligence, enabling businesses and consumers to benefit from open, high-impact AI systems. You will collaborate with a global, cross-functional team to design, build, and deploy models that solve real-world problems across reasoning, code, and multimodal applications. Your work will directly shape how AI integrates into daily life and enterprise operations. WHAT YOU WILL DO - Research and develop novel methods to advance the capabilities of LLMs. - Design and implement tooling and infrastructure for training, evaluating, and analysing AI models at scale. - Collaborate with scientists, engineers, and product teams to ship AI systems with tangible impact. - Explore and innovate across use cases such as reasoning, code generation, and agent-based systems. - Work with multimodal data, including text, image, and speech, to expand model capabilities. - Optimise distributed systems to improve the efficiency and scalability of model training. - Contribute to the open-source community by releasing frontier models for public use. WHAT WE'RE LOOKING FOR - A track record of contributing to relevant scientific domains, such as publications or open-source projects. - Hands-on experience with AI frameworks like PyTorch or JAX, or distributed systems such as Ray or Kubernetes. - Proficiency in at least one programming language, such as Python, Rust, Go, or Java. - Ability to design complex software systems and transition them into production environments. - Experience with training large transformer models in a distributed setting. - Familiarity with the full MLOps stack, including fine-tuning, evaluation, and deployment. - A self-starter mindset with the autonomy to drive projects forward and collaborate effectively in a team. - Strong engineering competence, with a focus on building scalable and reliable systems. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

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 The Fraud Prevention team protects Anthropic's payment and monetization surfaces from financial abuse — keeping fraud losses, dispute rates, and network monitoring exposure in check while preserving a smooth experience for legitimate customers. As a software engineer on this team, you will build the systems that make risk decisions in real time, manage the dispute and chargeback lifecycle, and detect monetization abuse across subscriptions, in-app purchases, and promotions. The ideal candidate can see things from attackers' perspectives, anticipate their responses to countermeasures, and never loses sight of the fact that a false positive here is a paying customer. Payments fraud is more externally coupled than most trust and safety work — you'll collaborate closely with finance, support, and legal teams internally, and with payment processors and platform partners externally. Responsibilities: Design and build real-time risk decisioning that scores transactions at authorization time, balancing fraud loss, approval rates, and latency constraints Build tooling and automation for the dispute and chargeback lifecycle, from review queues to evidence collection and loss reporting Engineer fraud signals at scale — device fingerprinting, BIN and issuer signals, velocity features, and cross-account linkage — and detect monetization abuse across subscriptions, trials, promotions, and in-app purchases Own a portfolio of metrics — loss rate, dispute rate, authorization approval impact, and false-positive rate — rather than optimizing any single number Lead investigations into emerging fraud patterns, building multi-layered defenses designed for attacker adaptation rather than point-in-time rules Work cross-functionally with finance, support, legal, and data science, and with external payment processors and platform partners Minimum Qualifications: Proficiency in Python, SQL, and data analysis tools Experience building or operating fraud, risk, or abuse detection systems in production Strong communication skills and ability to explain complex technical tradeoffs to non-technical stakeholders Preferred Qualifications: 8+ years of industry software engineering experience, with a focus on payments fraud or risk Fluency with payments rails: card networks, payment service providers (e.g., Stripe, Adyen), in-app purchase platforms (Apple, Google), refund flows, and the chargeback and dispute lifecycle Direct experience combating fraud typologies such as card testing, stolen-card monetization, refund and chargeback abuse, subscription and trial abuse, promotional abuse, and friendly fraud Understanding of fraud loss accounting — fraud loss vs. dispute fees vs. card network monitoring programs (e.g., VDMP, i VFMP, Mastercard ECP) — and why chargeback rate thresholds carry existential stakes Experience building hybrid rules-and-ML risk systems: real-time scoring at authorization plus post-authorization review workflows Experience at a marketplace or subscription business, or on a processor-side or issuer-side risk team 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.

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 Application Security team secures the systems that build, serve, and increasingly are Claude — and as Anthropic's footprint grows, that mandate now extends to companies and codebases we bring in from outside. This role establishes that function. You'll own security due diligence and secure integration for Anthropic's acquisitions — assessing a target's security posture pre-close, writing the security risk readout for leadership, and after close, bringing acquired systems up to Anthropic's bar. Security has been part of every deal to date, but this is the first dedicated role for it: you'll formalize the playbook, the risk model, and the tooling, and make them repeatable. This is an AppSec role first. You'll be an active member of the Application Security team — same rituals, same on-run rotation, same tooling, working alongside engineers securing Anthropic's own agentic product surfaces. The expectation is the same too: we use Claude as our primary tool, and you're expected to automate the repeatable parts of diligence and integration as you go, so each acquisition is easier than the last. When deal flow is quiet, you'll pick up core AppSec project work; when it's active, M&A is your priority. We're upfront that the center of gravity here is M&A rather than core product security. It's burstier, more assessment-heavy, and operates on confidential, time-sensitive work. If you like parachuting into an unfamiliar codebase under time pressure and turning it into a clear risk picture for leadership, this is that job. Key responsibilities Lead pre-close security due diligence on prospective acquisitions — coordinate external penetration testing, threat-model the target's architecture, assess security controls, and deliver the security risk readout for leadership ahead of close and integration planning Drive post-close security integration — stand up static and dynamic analysis coverage on acquired codebases, track high- and critical-severity remediation to closure, fold acquired assets into bug bounty scope, and onboard repositories to Anthropic's automated vulnerability remediation and reporting systems Coordinate adjacent security engineering teams (supply chain, cloud, corporate security, detection & response) on their portions of each integration Work across a wide set of stakeholders on every deal — corporate development, legal, security leadership, and the engineering teams inheriting acquired systems internally; engineering and security counterparts at the target company externally — translating between them and keeping the security workstream legible to all of them Formalize and scale Anthropic's M&A security playbook — risk-scoring model, diligence runbook, integration checklist — and turn as much of it as possible into Claude-powered tooling rather than manual process Share the team's operational on-run rotation (bug bounty escalations, launch consults, incident response), swapping out during periods of active deal work Contribute to core AppSec projects between deals — secure design reviews, threat modeling for agentic systems, and the team's security automation roadmap Minimum qualifications Hands-on application and infrastructure security experience, including cloud and containerized environments Demonstrated ability to rapidly assess an unfamiliar codebase or architecture and produce a clear, prioritized risk assessment for a non-security audience Production-quality coding ability in at least one of Python, Go, Rust, or TypeScript Practical threat-modeling and vulnerability-identification skills — you've found and reasoned about real bugs in real systems Comfort operating with high autonomy, ambiguity, and tightly-held confidential context Clear written and verbal communication across varied audiences — executives, legal and corporate development partners, and engineering counterparts at an acquired company Preferred qualifications 7+ years in application security, security consulting, or security architecture Prior M&A security due diligence, third-party security assessment, or technical due diligence experience Experience standing up or scaling SAST/DAST, bug bounty, or vulnerability management coverage across multiple codebases Track record of building security automation or tooling rather than relying solely on manual review Familiarity with using LLMs as a core part of your security workflow Experience securing agentic, code-execution, or LLM-integrated systems Representative projects Point Anthropic's internal LLM-driven code analysis and AI-assisted scanning at an acquired repository nobody here has seen, and turn the output into a prioritized remediation plan in days rather than weeks Design the risk-scoring framework Anthropic uses to compare security posture across acquisitions of different shapes and sizes Build the automation that onboards an acquired codebase to Anthropic's vulnerability dashboard, dependency auto-patching, and bounty scope without a human running a checklist Write the security risk memo for a live deal and present it to corporate development and security leadership 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.