Anthropic Research Resident

<div class="content-intro"><h2><strong>About Anthropic</strong></h2> <p>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.</p></div><h2><strong>About the role</strong></h2> <p>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 <strong>professor in a quantitative discipline, a technical founder or a staff-level engineer</strong> and want to transition to work on transformative AI, we want to hear from you. Background in machine learning is not required.</p> <h2><strong>What to expect</strong></h2> <ul> <li>A concrete, scoped project matched to your background, with direct mentorship from Anthropic researchers</li> <li>Access to Claude models and GPU compute</li> <li>Connection to the broader AI safety and security research community</li> </ul> <h2><strong>Interview process</strong></h2> <p>The interview process will include an initial application, recruiter screen, technical assessment, research discussion and a reference check.</p> <p>Applications for this round close on November 22, 2026 (11:59 PM PT). We expect to make offers in January 2027.</p> <h2><strong>You may be a good fit if you</strong></h2> <ul> <li>Are motivated by making sure AI is safe and beneficial for society as a whole</li> <li>Are excited to transition into working on empirical AI research full-time</li> <li>Have led ambitious work in a variety of technical fields (professor in a quantitative discipline, a technical founder or a staff-level engineer)</li> <li>Thrive in fast-paced, collaborative environments</li> <li>Can implement ideas quickly and communicate clearly</li> </ul> <h2><strong>Strong candidates may also</strong></h2> <ul> <li>Have experience authoring research papers in machine learning, NLP, or AI safety</li> <li>Have experience with LLMs, reinforcement learning or Kubernetes clusters and complex shared codebases</li> </ul> <h2><strong>Mentors and research areas</strong></h2> <p>Potential Anthropic mentors include:</p> <ul> <li><a href="https://www.linkedin.com/in/sara-price-310757b2/">Sara Price</a>: leads the Alignment Training team; background in data science</li> <li><a href="https://ethanperez.net/">Ethan Perez</a>: leads the Alignment Science team; background in machine learning</li> <li><a href="https://evhub.github.io/">Evan Hu