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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. 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.
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. Safeguards Acceleration: Builds the agentic systems that let Anthropic's trust & safety teams work at the speed of the models they're protecting. Our flagship project extends Claude Tag, Anthropic's agentic AI collaborator, so it can safely operate on the sensitive data at the heart of Safeguards work: investigating abuse, calibrating detection systems, and closing the loop from signal to enforcement. The hard part isn't making the agent capable, it's making it safe. We develop sandboxed agent architectures, brokered and audited data access, and provenance guarantees that keep humans firmly in control as model capabilities grow. You'll work at the intersection of agent security, privacy engineering, and safeguards infrastructure, on problems that get more important with every model release. Safeguards Interventions: Responsible for what happens when a safety system fires. You'll own the composable arsenal of intervention options that sit between our detection stack (classifiers and probes) and the user, across every Anthropic surface: 1P products, the API, and third-party clouds. This includes inline interventions for areas like harmful bio, cyber, and acceptable usage as well as downstream areas like child safety and copyright. You'll build sync and async systems that operate at Anthropic scale, touching every request, and ensuring that we evolve and drive the quality, scale and systems of our interventions to enable our products to grow safely. Safeguards Data Intelligence: Builds the systems that catch what everything else misses. Our Claude Investigation tool, an autonomous Claude-powered agent that reasons across tens of billions of stored interactions to surface cyberattacks, weapons development, and state-sponsored influence operations; thousands of copies run in parallel, which is how a small team covers the whole surface. The hard part isn't finding signal, it's finding it at this scale, under real deadlines, on threats that are actively adapting to us. You'll do serious distributed-systems and data-infrastructure work — running an agent fleet across three clouds, building batch inference, summarization, and search infrastructure — against threats that are happening today, not hypotheticals. 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 experience Proficiency in Python and Typescript 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. 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.
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. 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.
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. 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.
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. 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.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team The Security Engineering team protects Anthropic's AI systems and maintains the trust of our users and society. We define the authentication architecture for our training infrastructure, design the cryptographic foundations that protect model weights and training data, and drive the developer security program that shapes how engineers build and ship software. The team works across several areas that collaborate closely: identity and secrets management, developer security and supply chain, infrastructure security, and secure frameworks. You will support one of these areas while contributing across others, with your focus shaped by your strengths and the team's priorities. Responsibilities: Build and maintain identity and secrets management systems, including credential issuance, rotation, and workload authentication across our multi-cloud environments Contribute to cluster security controls including RBAC policies, namespace isolation, workload identity, and pod security Implement and maintain cloud security controls including IAM, network segmentation, VPC architecture, and encryption across our multi-cloud and on-prem environments Design and implement secure development frameworks and libraries that make secure coding the path of least resistance for our engineering teams, including service to service authentication, serialization libraries, and tool proxies. Harden CI/CD pipelines against supply chain attacks through isolated build environments, signed attestations, dependency verification, and automated policy enforcement Identify and remediate security gaps through code review, threat modeling, and hands-on debugging Contribute to continuous cloud security posture management using infrastructure-as-code scanning, misconfiguration detection, and automated remediation You may be a good fit if you have: At least 5 years of software engineering experience implementing and maintaining security-relevant systems in production Bachelor's degree in Computer Science or equivalent industry experience Strong programming skills in Python or at least one systems language such as Go or Rust Experience contributing to cloud security controls A track record of taking ownership of problems end to end, from identifying the issue to shipping and monitoring the fix Clear communication skills and the ability to work collaboratively across engineering teams Low ego and high empathy, with a genuine interest in helping teammates succeed Passion for AI safety and the role security engineering plays in building trustworthy AI systems Strong candidates may also have: Contributions to developer security tooling including SAST, dependency scanning, or secure build infrastructure Familiarity with Kubernetes security primitives including RBAC, namespaces, network policies, and admission controllers Experience with cloud security posture management tooling, infrastructure-as-code security scanning, or automated remediation Experience with network security and isolation techniques including east-west controls, traffic inspection, and cloud network policy Experience with eBPF for security monitoring and enforcement, or developing kernel security policies Experience building secrets management or workload authentication systems, including familiarity with protocols such as OAuth 2.0, OIDC, SAML, or SPIFFE/SPIRE Background building or operating security systems in environments that support research workflows and rapid iteration 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 — $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. 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.
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. Role Summary A systems-level engineer specializing in network infrastructure and network optimization, with expertise in building and maintaining software that interacts with networks. You will be responsible for writing and maintaining software that interfaces between our accelerators and our high-speed networks. This role requires deep technical knowledge of network protocols, kernel-space and/or user-space networks, interfacing with hardware, and the ability to debug and optimize distributed software at the network level. You may be a good fit if you have: Networking Systems Engineering: Expert-level proficiency with network protocols and networking concepts Deep kernel networking: TCP/IP stack internals, XDP, eBPF, io_uring, and epoll User-space networking: DPDK, RDMA, kernel bypass techniques Understanding of how to build higher-level abstractions like collectives and RPC Skilled at diagnosing and resolving networking issues in distributed systems, especially at OSI model layers 2-4 Low-Level Systems and OS Programming: Strong programming skills in a systems programming language, including memory management, lock-free data structures, and NUMA-aware programming Software, driver, and OS performance optimization tools and techniques Comfort with or desire to learn Rust Strong candidates may have: Understanding of ML accelerators and accelerator drivers Demonstrated ability to design new network protocols Experience with PCIe and drivers for PCIe devices Expertise in algorithms used in networking, including compression and graph algorithms Experience programming on SmartNICs 5+ years of experience in systems programming or network programming Often comes from backgrounds in: HPC, telecommunications, host networking software, OS/kernel engineering, or embedded systems Strong debugging mindset with patience for complex, multi-layered issues Representative Projects: Build a system for accelerator-initiated tensor movement over the network Benchmark software for a new networking environment Implement a new collective algorithm to improve latency Optimize congestion control algorithms for large-scale synchronous workloads Debug kernel-level network latency spikes The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $280,000 — $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. 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.
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: Pioneering the next generation of AI requires breakthrough innovations in GPU performance and systems engineering. As a GPU Performance Engineer, you'll architect and implement the foundational systems that power Claude and push the frontiers of what's possible with large language models. You'll be responsible for maximizing GPU utilization and performance at unprecedented scale, developing cutting-edge optimizations that directly enable new model capabilities and dramatically improve inference efficiency. Working at the intersection of hardware and software, you'll implement state-of-the-art techniques from custom kernel development to distributed system architectures. Your work will span the entire stack—from low-level tensor core optimizations to orchestrating thousands of GPUs in perfect synchronization. Strong candidates will have a track record of delivering transformative GPU performance improvements in production ML systems and will be excited to shape the future of AI infrastructure alongside world-class researchers and engineers. You might be a good fit if you: Have deep experience with GPU programming and optimization at scale Are impact-driven, passionate about delivering measurable performance breakthroughs Can navigate complex systems from hardware interfaces to high-level ML frameworks Enjoy collaborative problem-solving and pair programming Want to work on state-of-the-art language models with real-world impact Care about the societal impacts of your work Thrive in ambiguous environments where you define the path forward Strong candidates may also have experience with: GPU Kernel Development: CUDA, Triton, CUTLASS, Flash Attention, tensor core optimization ML Compilers & Frameworks: PyTorch/JAX internals, torch.compile, XLA, custom operators Performance Engineering: Kernel fusion, memory bandwidth optimization, profiling with Nsight Distributed Systems: NCCL, NVLink, collective communication, model parallelism Low-Precision: INT8/FP8 quantization, mixed-precision techniques Production Systems: Large-scale training infrastructure, fault tolerance, cluster orchestration Representative projects: Co-design attention mechanisms and algorithms for next-generation hardware architectures Develop custom kernels for emerging quantization formats and mixed-precision techniques Design distributed communication strategies for multi-node GPU clusters Optimize end-to-end training and inference pipelines for frontier language models Build performance modeling frameworks to predict and optimize GPU utilization Implement kernel fusion strategies to minimize memory bandwidth bottlenecks Create resilient systems for planet-scale distributed training infrastructure Profile and eliminate performance bottlenecks in production serving infrastructure Partner with hardware vendors to influence future accelerator capabilities and software stacks Deadline to apply: None. Applications will be reviewed on a rolling basis. The expected salary range for this position is: The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $280,000 — $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. 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.
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. 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.
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team Our team is organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. About the role As a Research Engineer on our team you will work end to end across the whole model stack, identifying and addressing key infra blockers on the path to scientific AGI. Strong candidates should have familiarity with elements of language model training, evaluation, and inference and eagerness to quickly dive and get up to speed in areas they are not yet an expert on. This may include performance optimization, distributed systems, VM/sandboxing/container deployment, and large scale data pipelines. Join us in our mission to develop advanced AI systems pushing the frontiers of science and benefiting humanity. Responsibilities: Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI. Build scalable and performant VM/sandboxing/container architectures to safely execute long-horizon AI tasks and scientific workflows Collaborate to translate experimental requirements into production-ready infrastructure Develop large scale data pipelines to handle advanced language model training requirements Optimize large scale training and inference pipelines for stable and efficient reinforcement learning You may be a good fit if you: Have 6+ years of highly-relevant experience in infrastructure engineering with demonstrated expertise in large-scale distributed systems Are a strong communicator and enjoy working collaboratively Possess deep knowledge of performance optimization techniques and system architectures for high-throughput ML workloads Have experience with containerization technologies (Docker, Kubernetes) and orchestration at scale Have proven track record of building large-scale data pipelines and distributed storage systems Excel at diagnosing and resolving complex infrastructure challenges in production environments Can work effectively across the full ML stack from data pipelines to performance optimization Have experience collaborating with other researchers to scale experimental ideas Thrive in fast-paced environments and can rapidly iterate from experimentation to production Strong candidates may also have: Experience with language model training infrastructure and distributed ML frameworks (PyTorch, JAX, etc.) Background in building infrastructure for AI research labs or large-scale ML organizations Knowledge of GPU/TPU architectures and language model inference optimization Experience with cloud platforms (AWS, GCP) at enterprise scale Familiarity with VM and container orchestration. Experience with workflow orchestration tools and experiment management systems History working with large scale reinforcement learning Comfort with large scale data pipelines (Beam, Spark, Dask, …) 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. 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.
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 seeking a seasoned Revenue Accounting professional to join our growing Accounting Team. In this position, you will drive revenue accounting operations, accounts receivable accounting, and financial reporting processes. You will play a critical role in ensuring accurate revenue recognition, managing complex AR processes including CECL compliance, and enhancing our month-end close operations. The ideal candidate brings deep technical accounting expertise, leadership capabilities, and thrives in our fast-paced, innovative environment. Responsibilities Manage daily revenue accounting operations, including high-volume transaction processing, and ensure accurate revenue recognition in compliance with ASC 606 Own the month-end revenue close process by reviewing and approving revenue-related account reconciliations and journal entries for revenue, deferred revenue, and unbilled receivables Manage comprehensive accounts receivable accounting functions, including AR reconciliations, aging analysis, and accurate recording of customer receivables Lead quarterly CECL aging analysis to ensure consistent application of ASC 326 and work with AR & Collections Lead to develop key AR metrics for management reporting Perform regular month-end close flux analysis, identifying and explaining significant variances in revenue and accounts receivable balances to ensure financial integrity and provide insights for management decision-making Collaborate cross-functionally with Finance Operations, Finance Strategy, Billing Support, and business partners on strategic processes and programs Support revenue accounting system initiatives, including design, implementation, testing, and optimization Serve as subject matter expert for revenue and AR accounting questions across the organization Lead audit coordination and serve as primary contact for external auditors during year-end audit Maintain comprehensive documentation for all revenue and AR processes You may be a good fit if you have Bachelor's degree in accounting or finance (or equivalent experience) 10+ years of accounting experience, with at least 3 years in public accounting Strong knowledge of ASC 606 Revenue from Contracts with Customers & ASC 326 Credit Impairment Experience with accounts receivable accounting and financial reporting Experience in collaborating across departments to influence change Attention to detail, excellent communication skills, and strong sense of teamwork Ability to work independently and prioritize in a fast-paced environment Strong sense of ownership and independence, with proven ability to identify issues, propose solutions, and drive initiatives to completion with minimal supervision Proven experience in managing and mentoring accounting professionals, with the potential to lead team members (both contractors and FTEs) as our team continues to grow Strong candidates may also have Experience in a growing SaaS technology business, preferably in startup or high-growth environments Experience with third-party platform revenue models and related accounting complexities Passion for data integrity, comfort with large datasets, and enjoyment of solving complex problems Proficiency with mainstream ERP systems and revenue engines such as NetSuite ARM, Oracle, SAP, Workday Financials and comparable systems. NetSuite ARM experience strongly preferred Experience with Metronome, Stripe, Anrok, or similar software is a plus Database & SQL experience is a plus Exceptional business acumen with ability to translate complex financial concepts into actionable insights for non-finance stakeholders The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $230,000 — $300,000 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. 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.
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 TPU Kernel Engineer, you'll be responsible for identifying and addressing performance issues across many different ML systems, including research, training, and inference. A significant portion of this work will involve designing and optimizing kernels for the TPU. You will also provide feedback to researchers about how model changes impact performance. Strong candidates will have a track record of solving large-scale systems problems and low-level optimization. You may be a good fit if you: Have significant experience optimizing ML systems for TPUs, GPUs, or other accelerators 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 Designing and implementing kernels for TPUs or other ML accelerators Understanding accelerators at a deep level, e.g. a background in computer architecture ML framework internals Language modeling with transformers Representative projects: Implement low-latency, high-throughput sampling for large language models Adapt existing models for low-precision inference Build quantitative models of system performance Design and implement custom collective communication algorithms Debug kernel performance at the assembly level The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $280,000 — $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. 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.