Anthropic Research Resident

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Anthropic Residency is our paid, fixed-term research program, with placements lasting between six weeks and six months. We are looking for people who have led ambitious work in a variety of technical fields and want to transition to full-time work focused on making sure AI systems are safe and beneficial for all of humanity. If you are a professor in a quantitative discipline, a technical founder or a staff-level engineer and want to transition to work on transformative AI, we want to hear from you. Background in machine learning is not required. What to expect A concrete, scoped project matched to your background, with direct mentorship from Anthropic researchers Access to Claude models and GPU compute Connection to the broader AI safety and security research community Interview process The interview process will include an initial application, recruiter screen, technical assessment, research discussion and a reference check. Applications for this round close on November 22, 2026 (11:59 PM PT). We expect to make offers in January 2027. You may be a good fit if you Are motivated by making sure AI is safe and beneficial for society as a whole Are excited to transition into working on empirical AI research full-time Have led ambitious work in a variety of technical fields (professor in a quantitative discipline, a technical founder or a staff-level engineer) Thrive in fast-paced, collaborative environments Can implement ideas quickly and communicate clearly Strong candidates may also Have experience authoring research papers in machine learning, NLP, or AI safety Have experience with LLMs, reinforcement learning or Kubernetes clusters and complex shared codebases Mentors and research areas Potential Anthropic mentors include: Sara Price : leads the Alignment Training team; background in data science Ethan Perez : leads the Alignment Science team; background in machine learning Evan Hubinger : leads the Alignment Stress-Testing team; formerly at The Machine Intelligence Research Institute (MIRI) Samuel Marks : leads the Scalable Oversight team; background in mathematics Elana Simon : researches the interpretability of language models and biological models; background in biomedical informatics Belinda Li : researches how language models represent the world, users, and themselves; background in natural language processing (PhD, MIT) Jack Lindsey : leads the Model Psychology team; background in theoretical neuroscience Nicholas Carlini : researches adversarial machine learning and AI security; previously at DeepMind and Google Brain Jascha Sohl-Dickstein : works at the intersection of safety and pretraining; background in physics and neuroscience, formerly Principal Scientist at Google Brain Residents will work on empirical research questions in collaboration with Anthropic's research teams. Areas we are particularly interested in include: AI safety & alignment Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains. Adversarial Robustness and AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. Model Organisms: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise. Model Internals and Interpretability: Advancing our understanding of the internal workings of large language models to enable more targeted interventions and safety measures. Safeguards Research: Developing robust defenses against adversarial attacks, comprehensive evaluation frameworks for model safety, and automated systems to detect and mitigate potential risks before deployment. AI Welfare: Improving our understanding of potential AI welfare and developing related evaluations and mitigations. AI security & frontier red-teaming Stress-testing frontier models to understand the full extent of their current capabilities in fields such as cybersecurity, robotics or cryptography. ML systems & reinforcement learning Improving how frontier models are trained and building the infrastructure behind that research, from model architecture, optimizers and training data to accelerator simulators, hardware backends and RL environment pipelines. For a fuller picture of the questions we care about, see our Recommendations for Technical AI Safety Research Directions and recent publications from our Alignment , Interpretability and Frontier Red teams. Logistics Duration: Placements are six weeks, three months or six months, depending on team fit and candidate preferences. Other lengths between three and six months are possible by exception. Location: We prefer that Residents work from our San Francisco office, where most of our research staff is based, but remote participation is possible, especially for shorter placements. Most full-time research roles at Anthropic require relocation to San Francisco. Remote participants need to be based in a country where Anthropic can hire. Commitment: Full-time role for the duration of the residency. Compensation: $350,000 to $500,000/year pro-rated for the duration of the residency + benefits Visa sponsorship: We sponsor visas for placements of three months or longer. For six-week placements we encourage remote participation from a country where Anthropic can hire. Applicants may also be considered for the Anthropic Fellows Program . 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.