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