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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 As a Manager on the AI-Native GTM team at Anthropic, you'll lead a team of 5-10 Growth Account Executives responsible for driving expansion and retention across our fastest-growing AI-Native customers. You'll build and develop a high-performing team while establishing the frameworks, processes, and best practices that enable them to help customers harness the transformative potential of safe, frontier AI. In this role, you'll be responsible for growing team revenue, driving optimal commercial outcomes, and ensuring Anthropic is building long-term partnerships with the world’s fastest growing AI native startups. Responsibilities: Lead, coach, and develop a team of 5-10 Account Executives, providing regular feedback and guidance to drive both individual and team performance Own team revenue targets, developing strategies to accelerate growth Build scalable frameworks and processes for deal negotiations, account planning, quarterly business reviews, and customer health monitoring Partner with Product, Marketing, and other GTM teams to identify and execute on strategic growth opportunities across the startup portfolio Regularly review customer health metrics and collaborate with team members to develop action plans for at-risk accounts Mentor team members in developing consultative sales skills, negotiation best practices, and technical understanding of AI applications Drive operational excellence through pipeline management, forecasting accuracy, and team productivity metrics Participate in strategic customer conversations and support Growth AEs in complex negotiations You may be a good fit if you have: 10+ years of experience in enterprise software sales or account management, with 3+ years leading sales teams Proven track record of consistently exceeding team revenue targets and developing high-performing account executives Strong understanding of the startup ecosystem and experience working with high-growth technology companies Deep expertise in strategic account planning and scaling account management processes in a fast-paced environment Strong analytical and problem-solving skills with a data-driven approach to decision making Excellence in cross-functional collaboration and stakeholder management Background in technical product sales, particularly in areas like APIs, infrastructure, or ML/AI solutions Demonstrated ability to coach and develop talent while maintaining high performance standards 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: $380,000 — $450,000 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 is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Staff level Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. Responsibilities Design and implement data processing infrastructure for large language model training (highly performant, reproducible, traceable) Develop and maintain core processing primitives (e.g., tokenization, deduplication, chunking) with a focus on scalability Build robust systems for data quality assurance and validation at scale Collaborate with research teams to implement novel data processing architectures Build and operate end-to-end data pipelines that turn raw web-scale corpora into training-ready datasets You may be a good fit if you have: 5+ YOE outside of internships Strong software engineering skills with experience building high-throughput fault-tolerant distributed systems Hands-on experience with distributed computing frameworks, particularly Apache Spark Excellent problem-solving skills and attention to detail Strong communication skills and ability to work in a collaborative environment Advanced degree in Computer Science or related field Experience with language model training infrastructure Background in Data Infrastructure, MLOps, or ML infrastructure Strong candidates may have: Have significant experience building high-throughput fault-tolerant distributed systems Expertise with Python and Rust Passionate about system reliability and performance Are comfortable working with ambiguous requirements and evolving specifications Take ownership of problems and drive solutions independently Are excited about contributing to the development of safe and ethical AI systems Can balance technical excellence with practical delivery Are eager to learn about machine learning research and its infrastructure requirements Sample Projects Designing and implementing distributed computing architecture for web-scale data processing Building scalable infrastructure for model training data preparation Developing fault-tolerant distributed processing systems Implementing new infrastructure components based on research requirements The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Berlin, Germany Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. Speed is something we fight for every day at Fin, and we believe Berlin is built for people who share that instinct. We are drawn to Berlin by its rare blend of deep technical talent and rich creative culture – all within a vibrant, globally connected city that’s close to our R&D hubs in Dublin and London. It’s a place where the best of the best technical talent thrive, and where people from around the world are eager to relocate and build ambitious products. Our ambition is to hire 100 people in Berlin over the year ahead across engineering, AI, data science, product, and design. We believe this is the most exciting time to join, be the founding R&D talent in the region and make a lasting impact as we build the world's number one customer agent! What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Identify areas where ML can create value for our customers Identify the right ML framing of product problems Working with teammates and Product and Design stakeholders Conduct exploratory data analysis and research Deeply understand the problem area Research and identify the right algorithms and tools Being pragmatic, but innovating right to the cutting-edge when needed Perform offline evaluation to gather evidence an algorithm will work Work with engineers to bring prototypes to production Plan, measure & socialize learnings to inform iteration Partner deeply with the rest of team, and others, to build excellent ML products What skills might I need? Broad applied machine learning knowledge 3-5 years applied ML experience Practical stats knowledge (experiment design, dealing with confounding etc) Intermediate programming skills Strong communication skills, both within engineering teams and across disciplines. Comfort with ambiguity Typically have advanced education in ML or related field (e.g. MSc) Scientific thinking skills Bonus skills & attributes Track record shipping ML products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Visualization, data skills, SQL, matplotlib, etc. Benefits We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! Competitive salary, annual bonus and equity Regular compensation reviews - we reward great work! Generous paid time off above statutory minimum Generous family leave (maternity, paternity), to let you spend valuable time with your loved ones Hybrid working MacBooks are our standard, but we also offer Windows for certain roles when needed. Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated Fun events for employees, friends, and family! Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

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's Infrastructure organization builds and operates the distributed systems that train, serve, and secure our AI models, including data pipelines, some of the largest Kubernetes clusters in the world, along with the databases, observability, and developer tooling that every other team at Anthropic depends on. As a Staff+ Software Engineer on our Infrastructure team, you'll independently scope and lead complex, multi-month infrastructure projects, make the architectural decisions other engineers build on, and work closely with research and product teams to understand their needs and build systems that keep pace as those needs evolve. Team placement happens after the interview process, based on your interests and experience alongside organizational needs. This lets us match you with the team where you'll have the most impact. Key responsibilities Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system Make architectural decisions that shape the foundation of infrastructure other engineers and teams build on Drive alignment on technical direction across multiple teams, working through ambiguous problem spaces Partner with research and product teams to understand their infrastructure and compute needs, and translate them into technical designs Take ownership of the reliability, scalability, and security of the systems you build as usage and complexity grow Set technical strategy and standards for your team's infrastructure Build and improve operational processes, such as incident response, postmortems, and on-call rotations, that help the team learn from every incident Mentor other engineers and help raise the technical bar for the team Minimum qualifications Experience designing, building, and operating large-scale distributed systems or infrastructure in production A track record of independently scoping and delivering complex, ambiguous, multi-month technical projects Experience making architectural decisions that other engineers and teams build on top of Strong software engineering fundamentals and proficiency in at least one programming language (for example, Python, Rust, Go, or Java) Experience with modern cloud infrastructure, including Kubernetes and infrastructure-as-code, on AWS and/or GCP Strong written and verbal communication skills, with experience driving alignment across multiple teams or stakeholders Preferred qualifications 10+ years of software engineering experience, not including internships Experience with machine learning infrastructure, such as GPUs, TPUs, or Trainium, and associated networking infrastructure like NCCL Low-level systems experience, such as Linux kernel tuning or eBPF Background in security or privacy engineering best practices Prior experience as a technical lead or mentor for other engineers Deadline to apply: None. Applications are reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $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 | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Reinforcement learning (RL) is how Claude learns to reason, write code, and act autonomously over long horizons. This role sits on the team that builds and owns the RL training system: the system that trains our production models and that researchers across Anthropic run their experiments on. The team works closely with research teams across the company on the science and engineering of making RL work at scale. As a Research Engineer on the team, you'll work at the center of RL at Anthropic. You'll have a direct view of how RL training behaves at the frontier because the system you own sits underneath both production and research runs. You will use it with collaborators across research teams to understand what is working, what is fragile, and where the next improvements are. Key responsibilities Build, own, and improve the core RL training system that serves Anthropic's production and research runs Work across the stack (orchestration, environments, training, inference, evaluation) wherever the system needs it Study how RL training behaves at scale and contribute to the research that improves it, in collaboration with teams across Anthropic Implement new training methods as stable, fast, well-tested code Improve the speed and efficiency of RL training and evaluation through profiling, optimization, and benchmarking Make the system easier for researchers to build on, through clean abstractions, clear APIs, and automated testing Debug hard problems across the stack, from a run that has quietly drifted to a distributed systems failure that only shows up at scale Communicate results clearly, in writing and in discussion Minimum qualifications Proficiency in Python and experience working in, debugging, and improving a large ML codebase Experience with large-scale machine learning training (reinforcement learning, pretraining, or post-training) or the systems that support it Experience with at least one modern ML framework (JAX, PyTorch, or similar) Ability to design controlled experiments and reach conclusions you and others can trust Ability to balance research exploration with engineering implementation Strong written and verbal communication skills Care about the societal impacts of your work and are committed to developing safe and beneficial systems Preferred qualifications Experience with reinforcement learning for large language models, in research, production, or both Experience studying training at scale: scaling behavior, training dynamics, or method development on large models Experience with large-scale distributed training systems Familiarity with LLM architectures and training methodologies Experience working close to a frontier training run Experience profiling and optimizing the performance of ML workloads Experience with RL environments, evaluations, or sandboxed code execution Experience with Rust or C++ Enjoy pair programming (we love to pair!) The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are looking for software engineers to help build safety and oversight mechanisms for our AI systems. As a software engineer on the Safeguards team, you will work to monitor models, prevent misuse, and ensure user well-being. This role will focus on building systems to detect unwanted model behaviors and prevent disallowed use of models. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies. We have multiple teams that are currently hiring within Safeguards. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers where they'll have the greatest impact and growth potential. Responsibilities: Develop monitoring systems to detect unwanted behaviors from our API partners and potentially take automated enforcement actions; surface these in internal dashboards to analysts for manual review Build abuse detection mechanisms and infrastructure Surface abuse patterns to our research teams to harden models at the training stage Build robust and reliable multi-layered defenses for real-time improvement of safety mechanisms that work at scale You may be a good fit if you: Bachelor’s degree in Computer Science, Software Engineering or comparable professional experience Proficiency in at least one programming language such as Python, Java, etc. Ability to work across the stack Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders Strong candidates may also: 8+ years of experience in a software engineering position Have experience with integrity, spam, fraud, or abuse detection and mitigation Have experience building trust and safety detection mechanisms and intervention for AI/ML systems Have experience with prompt engineering, jailbreak attacks, and other adversarial inputs Have worked closely with operational teams to build custom internal tooling Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $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: Jeddah, Saudi Arabia; Riyadh, Saudi Arabia; Al Khobar, Saudi Arabia; Yanbu, Saudi Arabia; Tabuk, Saudi Arabia; Madinah, Saudi Arabia Eram Talent is excited to announce an opening for a Data Program Analyst in Saudi Arabia. In this critical role, you will be responsible for analyzing and managing data programs to support decision-making and operational efficiency. The Program Analyst will transform raw data into actionable insights, helping us measure our impact, improve our programs, and make data-driven decisions. This position requires a strong analytical mindset and the ability to work collaboratively with various teams to enhance data-driven strategies. Key Responsibilities Data Capture & Management - Collect and maintain accurate data from participating startups and program activities. - Ensure completeness, consistency, and reliability of data across multiple programs. - Develop templates and processes for systematic data collection and verification. - Generate ad-hoc reports and data analysis to support strategic planning, business development, and program improvements. - Serve as the primary point of contact for startups regarding all data collection and reporting requirements. Program Support & Analysis Support program managers in planning and executing core activities (bootcamps, workshops, demo days, etc.). Track program delivery against timelines and escalate risks or delays. Contribute to preparation of program briefs, meeting notes, and stakeholder updates. Dashboard Development & Reporting Build and maintain dashboards to track KPIs, startup metrics, and ecosystem impact. Support the preparation of presentations with clear data visualizations and insights Startup Engagement & Program Support Proactively follow up with founders and team members to ensure timely submission of data and reports Support the onboarding of new startups into our data systems and reporting frameworks Requirements Bachelor's degree in Business, Economics, Data Science, or a related field is required. 2–4 years of professional experience in data analysis, program management support, or within startup/innovation ecosystems. Demonstrated ability to manage datasets with an extremely high level of accuracy and attention to detail required Proficiency in SQL, data visualization tools (e.g., Power BI, Tableau), and Excel. Demonstrated ability to manage datasets with an extremely high level of accuracy and attention to detail required. Strong analytical and problem-solving skills with attention to detail. Excellent communication skills, both verbal and written. Ability to work collaboratively in a team environment. Experience with data governance and data management frameworks is a plus. Fluency in English is required; proficiency in Arabic is an advantage.

Location: New York City, NY; New York City, NY | Seattle, WA; 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. You want to build large scale ML systems from the ground up. You care about making safe, steerable, trustworthy systems. As a Research Engineer, you'll touch all parts of our code and infrastructure, whether that's making the cluster more reliable for our big jobs, improving throughput and efficiency, running and designing scientific experiments, or improving our dev tooling. You're excited to write code when you understand the research context and more broadly why it's important. Note: This is an "evergreen" role that we keep open on an ongoing basis. We receive many applications for this position, and you may not hear back from us directly if we do not currently have an open role on any of our teams that matches your skills and experience. We encourage you to apply despite this, as we are continually evaluating for top talent to join our team. You are also welcome to reapply as you gain more experience, but we suggest only reapplying once per year. We may also put up separate, team-specific job postings . In those cases, the teams will give preference to candidates who apply to the team-specific postings, so if you are interested in a specific team please make sure to check for team-specific job postings! You may be a good fit if you: Have significant software engineering experience Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Enjoy pair programming (we love to pair!) Want to learn more about machine learning research Care about the societal impacts of your work Strong candidates may also have experience with: High performance, large-scale ML systems GPUs, Kubernetes, Pytorch, or OS internals Language modeling with transformers Reinforcement learning Large-scale ETL Representative projects: Optimizing the throughput of a new attention mechanism Comparing the compute efficiency of two Transformer variants Making a Wikipedia dataset in a format models can easily consume Scaling a distributed training job to thousands of GPUs Writing a design doc for fault tolerance strategies Creating an interactive visualization of attention between tokens in a language model 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: $350,000 — $500,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are looking for ML Engineers and Research Engineers to help detect and mitigate misuse of our AI systems. As a member of the Safeguards ML team, you will build systems that identify harmful use—from individual policy violations to sophisticated, coordinated attacks—and develop defenses that keep our products safe as capabilities advance. You will also work on systems that protect user wellbeing and ensure our models behave appropriately across a wide range of contexts. This work feeds directly into Anthropic's Responsible Scaling Policy commitments. Responsibilities Develop classifiers to detect misuse and anomalous behavior at scale. This includes developing synthetic data pipelines for training classifiers and methods to automatically source representative evaluations to iterate on Build systems to monitor for harms that span multiple exchanges, such as coordinated cyber attacks and influence operations, and develop new methods for aggregating and analyzing signals across contexts Evaluate and improve the safety of agentic products—developing both threat models and environments to test for agentic risks, and developing and deploying mitigations for prompt injection attacks Conduct research on automated red-teaming, adversarial robustness, and other research that helps test for or find misuse You may be a good fit if you Have 4+ years of experience in ML engineering, research engineering, or applied research, in academia or industry Have proficiency in Python and experience building ML systems Are comfortable working across the research-to-deployment pipeline, from exploratory experiments to production systems Are worried about misuse risks of AI systems, and want to work to mitigate them Have strong communication skills and ability to explain complex technical concepts to non-technical stakeholders Strong candidates may also have experience with Language modeling and transformers Building classifiers, anomaly detection systems, or behavioral ML Adversarial machine learning or red-teaming Interpretability or probes Reinforcement learning High-performance, large-scale ML systems 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: $350,000 — $500,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW At Harvey, we’re transforming how legal and professional services operate – not incrementally, but end-to end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. As we scale, our Enterprise Product organization sits at the center of this mission — connecting the systems our customers use, and scaling into new customer segments & verticals. We’re looking for a Product Manager with a strong technical foundation and the ability to own and solve complex product and commercial challenges end-to-end. This person will focus on building out integrations with strategic partners and vendors as well as enable search over data source using MCP’s and deep research. You will help architect systems to bring legal context into Harvey and also work with our Partnerships org and internal teams to prioritize which ones to build. This role is equal parts product intuition and technical execution. You’ll be trusted to make fast, high-quality decisions, ship impactful features, work on the cutting edge of applied AI and grow a team that embodies engineering excellence We move with urgency, bias toward simplicity, and expect our leaders to be hands-on when needed. If you’re energized by ownership, decisive execution, and solving real user problems, we'd love to hear from you. This role is based in San Francisco, CA. We use an in-person work model (3 days a week) and offer relocation assistance to new employees. WHAT YOU'LL DO - Lead the end-to-end product lifecycle, from ideation and strategy to execution and launch - Collaborate closely with engineering and partnerships team to identify and execute on high-impact integrations - Work closely with engineers to build, platformize and scale integrations, working cross functionally with adjacent teams - Expand the breadth and depth of integrations into the Harvey platform - Collaborate cross-functionally with Product Engineering, Applied AI, Research, and Platform teams to deliver high-quality production systems that support reasoning, summarization, and legal research workflows. WHAT YOU HAVE - 5+ years of experience building enterprise products in a B2B/commercial environment - Experience working on Integrations and partnering with cross functional and Partnerships teams - Experience with or knowledge of AI and LLMs - Ability to partner with engineers on technical architecture, with enough depth to challenge assumptions, propose solutions, and influence design. - Ability to navigate extreme ambiguity to deliver outcomes - A product mindset for balancing user needs, domain complexity, and system constraints to propose high-leverage improvements. COMPENSATION RANGE $215,000 - $300,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES [HERE https://www.notion.so/harveyai/Harvey-Candidate-Privacy-Policies-319ac3fcdd7a803bb807d5094f249922]. #LI-ML1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: Sofia, Bulgaria About Wolt At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we’re building the delivery of (almost) everything and you’ll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe. Working at Wolt isn’t always easy, but it’s definitely exciting. Here you’ll learn more, build more, and ship more than in most other companies. You’ll be challenged a lot, but also have a lot of fun on the way. So, if you’re a self-starter with drive and entrepreneurial spirit, this could be the ride of your life. Are you a team player with great communication skills? Do you enjoy working in a dynamic environment? If your answer is yes, then read further! 🤩 We are looking for full-time Support Associates to join our Support team in Bulgaria! What you'll be doing Supporting our customers, courier partners, and venues via live chat and phone for Bulgarian market Ensure that the delivery operations run smoothly Developing our support function together with the support team as well as other teams within Wolt Our humble expectations You have great communication skills with a personal touch and a customer-obsessed and team-oriented mindset You are a fast learner, you have no problem with multitasking, and you are ready to work in a fast-paced environment You can work in shifts in mornings, evenings, and weekends - our support is open seven days a week You will work directly from the office You are fluent in Bulgarian and English Next steps All our Support Associates work directly from our office, and we do not provide the possibility to work from home. If you are excited about working in a high-growth environment, taking ownership, and being part of an extremely ambitious team, then click below to apply and get the conversation going! We will be reviewing applications on an on-going basis, so send through your application along with your CV as soon as possible! 💙 Our Commitment to Diversity and Inclusion We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. Beware of recruitment scams: DoorDash, Deliveroo, and Wolt will never ask you to pay money or share sensitive financial information during hiring — learn more about our legitimate recruiting process at Recruitment Scam Awareness - DoorDash .

Location: San Francisco, CA | 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 is looking for a talented AI Research Recruiter to partner with our Research teams. In this pivotal role, 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. Responsibilities: Develop and execute strategic recruiting plans to identify, source, and hire highly qualified candidates, with a focus on Machine Learning and AI research talent Partner with Research hiring managers and interviewers to understand hiring needs, team matching, required skills and qualifications Enhance and implement recruiting processes and programs while maintaining an inclusive and high talent bar, 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 within the research and science community to showcase our mission, culture, and values to candidates Stay up-to-date on recruiting best practices, emerging sourcing techniques, interview innovations, and workplace trends You may be a good fit if you: Have 5+ years of experience in full life cycle recruiting supporting technical research teams Have a passion for AI's potential to positively impact the world and realistic assessment of its risks and limitations Are experimental and are open to new, creative recruiting ideas, or have experience working with hiring managers who are open to non-traditional talent strategies Thrive in fast-paced, dynamic environments and enjoy juggling multiple priorities Possess strong technical aptitude with the ability to understand and evaluate technical qualifications Have enthusiasm for deeply understanding the needs of researchers and innovating on recruiting processes to make them more tailored to the world of research Have excellent organizational skills and attention to detail, as well as a proactive mindset and ability to operate with autonomy Have experience partnering with researchers and hiring talent that work on GenAI and LLMs Have a proven track record of scaling and building diverse and high-performing teams in a fast-paced, high-growth startup environment Strong candidates may also: Bring a deep interest in AI safety research Have experience partnering with researchers and hiring talent that work on GenAI and LLMs Have experience with academic recruitment and research communities 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: $175,000 — $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: London, UK 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 ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems. This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow. Responsibilities: Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams Build and maintain production logging, monitoring dashboards, and evaluation infrastructure Add new capabilities to the training codebase, such as long context support or novel architectures Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned You May Be a Good Fit If You: Have hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems Genuinely enjoy both research and engineering work—you'd describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other Are excited about being on-call for production systems, working long days during launches, and solving hard problems under pressure Thrive when working on whatever is most impactful, even if that changes day-to-day based on what the production model needs Excel at debugging complex, ambiguous problems across multiple layers of the stack Communicate clearly and collaborate effectively, especially when coordinating across time zones or during high-stress incidents Are passionate about the work itself and want to refine your craft as a research engineer Care about the societal impacts of AI and responsible scaling Strong Candidates May Also Have: Previous experience training LLM’s or working extensively with JAX/TPU, PyTorch, or other ML frameworks at scale Contributed to open-source LLM frameworks (e.g., open_lm, llm-foundry, mesh-transformer-jax) Published research on model training, scaling laws, or ML systems Experience with production ML systems, observability tools, or evaluation infrastructure Background as a systems engineer, quant, or in other roles requiring both technical depth and operational excellence What Makes This Role Unique: This is not a typical research engineering role. The work is highly operational—you'll be deeply involved in keeping our production models training smoothly, which means being responsive to incidents, flexible about priorities, and comfortable with uncertainty. During launches, the team often works extended hours and may need to respond to issues on evenings and weekends. However, this operational intensity comes with extraordinary learning opportunities. You'll gain hands-on experience with some of the largest, most sophisticated training runs in the industry. You'll work alongside world-class researchers and engineers, and the institutional knowledge you build will compound in ways that can't be easily transferred. For people who thrive on this type of work, it's uniquely rewarding. We're building a close-knit team of people who genuinely care about doing excellent work together. If you're someone who wants to be part of training the models that will define the future of AI—and you're excited about the full reality of what that entails—we'd love to hear from you. Location: This role requires working in-office 5 days per week in London. Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: £260,000 — £630,000 GBP 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 ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems. This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow. Responsibilities: Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams Build and maintain production logging, monitoring dashboards, and evaluation infrastructure Add new capabilities to the training codebase, such as long context support or novel architectures Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned You May Be a Good Fit If You: Have hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems Genuinely enjoy both research and engineering work—you'd describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other Are excited about being on-call for production systems, working long days during launches, and solving hard problems under pressure Thrive when working on whatever is most impactful, even if that changes day-to-day based on what the production model needs Excel at debugging complex, ambiguous problems across multiple layers of the stack Communicate clearly and collaborate effectively, especially when coordinating across time zones or during high-stress incidents Are passionate about the work itself and want to refine your craft as a research engineer Care about the societal impacts of AI and responsible scaling Strong Candidates May Also Have: Previous experience training LLM’s or working extensively with JAX/TPU, PyTorch, or other ML frameworks at scale Contributed to open-source LLM frameworks (e.g., open_lm, llm-foundry, mesh-transformer-jax) Published research on model training, scaling laws, or ML systems Experience with production ML systems, observability tools, or evaluation infrastructure Background as a systems engineer, quant, or in other roles requiring both technical depth and operational excellence What Makes This Role Unique: This is not a typical research engineering role. The work is highly operational—you'll be deeply involved in keeping our production models training smoothly, which means being responsive to incidents, flexible about priorities, and comfortable with uncertainty. During launches, the team often works extended hours and may need to respond to issues on evenings and weekends. However, this operational intensity comes with extraordinary learning opportunities. You'll gain hands-on experience with some of the largest, most sophisticated training runs in the industry. You'll work alongside world-class researchers and engineers, and the institutional knowledge you build will compound in ways that can't be easily transferred. For people who thrive on this type of work, it's uniquely rewarding. We're building a close-knit team of people who genuinely care about doing excellent work together. If you're someone who wants to be part of training the models that will define the future of AI—and you're excited about the full reality of what that entails—we'd love to hear from you. Location: This role requires working in-office 5 days per week in San Francisco. Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY 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 Mid-Market Account Executive on Anthropic's Industries team, you'll drive the adoption of safe, frontier AI by securing strategic deals with mid-market companies in key verticals, unlocking new value streams throughout their business. You'll leverage your consultative sales expertise and technical acumen to propel revenue growth while becoming a trusted partner to customers, helping them embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM, Product, Engineering, and cross-functional teams, you'll continuously refine our value proposition, sales methodology, and market positioning to ensure differentiated value across the landscape. You will be contributing to the GTM strategy for our Industries team, focusing on sector-specific solutions and strategies within key verticals. In addition, the Mid-Market team is pioneering a new scaled sales playbook, where human AEs direct AI Agents to automate key elements of the buyer’s journey, while maintaining human engagement with prospects in the elements of a sales process that can’t be automated. You should be passionate about building a fundamentally new sales motion, by experimenting with new programs and workflows, and ultimately evangelizing the potential of Transformative AI to mid-market companies across verticals. Responsibilities: Contribute to the Mid-Market GTM strategy, identifying new use cases within your assigned verticals, winning new business, and sharing feedback with cross-functional teams Drive strategic expansion within key accounts in established verticals and new logo acquisition within emerging verticals Own a revenue target and all aspects of the sales cycle from prospecting to close, including finding key workflows to automate and agentify Become a trusted advisor to customers, understanding their unique needs and crafting tailored AI solutions. Co-innovate with customers and sell on the product roadmap while appropriately setting expectations Collaborate extensively with cross-functional partners including Product, Customer Success, Legal, Marketing, and Applied AI to help bring new solutions to market and provide feedback to shape roadmaps Develop sales collateral, proposals, and presentations to effectively position Anthropic's AI products. Continuously refine sales tactics and share best practices You may be a good fit if you have: 3+ years of enterprise B2B sales experience in technology, preferably in SaaS, API solutions, or emerging technologies Experience automating workflows or building automations to handle the repeatable components of a sales process Proven experience exceeding revenue targets in fast-paced organizations by effectively managing an evolving pipeline and sales process Excellent communication skills and the ability to present confidently and build connections across all customer levels, from ICs to C-level executives A knack for bringing order to chaos and an enthusiastic “roll up your sleeves'' mentality. You are a true team player A strategic, analytical approach to assessing markets combined with creative, tactical execution to capture opportunities A passion for and/or experience with advanced AI systems. You feel strongly about ensuring frontier AI systems are developed safely Location: This role does require being in office 4x a week in one of our hubs 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 — $360,000 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: London, England Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Play an active role in hiring, mentoring and career development of other engineers Raise the bar for technical standards, performance, reliability, and operational excellence Identify areas where ML can create value for our customers Identify the right ML framing of product problems - Working with teammates and Product and Design stakeholders Conduct exploratory data analysis and research - Deeply understand the problem area Research and identify the right algorithms and tools - Being pragmatic, but innovating right to the cutting-edge when needed Perform offline evaluation to gather evidence an algorithm will work Work with engineers to bring prototypes to production Plan, measure & socialize learnings to inform iteration Partner deeply with the rest of team, and others, to build excellent ML products What skills might I need? 5-8 years applied ML experience Previous background in a senior/staff role (data science, software development or academic) Significant, demonstrated impact that your work has had on the product and/or the teams Strong programming skills Experience as the primary technical leader for a team Strong communication skills, both within engineering teams and across disciplines. Comfort with ambiguity Typically have advanced education in ML or related field (e.g. MSc) Scientific thinking skills Bonus skills & attributes Track record shipping ML products PhD or other experience in a research environment Deep experience in an applicable ML area - E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Visualization, data skills, SQL, matplotlib, etc. Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Location: London, England Fin , now part of Salesforce, is on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system. Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI. Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Identify areas where ML can create value for our customers Identify the right ML framing of product problems Working with teammates and Product and Design stakeholders Conduct exploratory data analysis and research Deeply understand the problem area Research and identify the right algorithms and tools Being pragmatic, but innovating right to the cutting-edge when needed Perform offline evaluation to gather evidence an algorithm will work Work with engineers to bring prototypes to production Plan, measure & socialize learnings to inform iteration Partner deeply with the rest of team, and others, to build excellent ML products What skills might I need? Broad applied machine learning knowledge 3-5 years applied ML experience Practical stats knowledge (experiment design, dealing with confounding etc) Intermediate programming skills Strong communication skills, both within engineering teams and across disciplines. Comfort with ambiguity Typically have advanced education in ML or related field (e.g. MSc) Scientific thinking skills Bonus skills & attributes Track record shipping ML products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Visualization, data skills, SQL, matplotlib, etc. Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers . Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. Policies Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week. We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values . Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

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 We're looking for seasoned iOS engineers to join our Claude mobile product team and help build apps that harness the transformative power of advanced language models. Our mission is to unlock the potential of advanced AI through elegant, user-friendly mobile applications that put unprecedented capabilities at users' fingertips. You will work with a talented team of engineers, researchers, design and Product teams to design and implement key components of our products. Join us in this exciting mission to transform how people engage with technology and unlock new realms of human potential. Key r esponsibilities Architect and implement cutting-edge iOS applications Develop novel solutions leveraging AI technologies Optimize performance at all levels of the mobile stack Champion best practices in mobile development Obsessive attention to detail and app experience Contribute to backend systems as needed Originate new product bets and own them from idea to launch Cut a vague direction down to the leanest real version one Minimum qualifications Expertise in Swift, UIKit, SwiftUI, and iOS frameworks Proficiency with the latest mobile platform capabilities and intricacies Practical experience with full-stack development and comfort working with backend technologies A track record of shipping impactful, high-adoption mobile applications Strong communication and mentorship skills Thrived in a fast-paced, collaborative environment and and enjoy working closely with cross functional partners and teammates Preferred qualifications 0-to-1 experience building successful products in early-stage environments Experience building applications that utilize modern ML/AI technology 3D graphics, visual effects, and audio and video streaming on mobile A vision for the future of human-machine interaction and a drive to make that vision a reality 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.