Research Scientist, Takeoff Intel

<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>About the role</h2> <p>We're looking for a Research Scientist who has done hands-on research on large models (pretraining, fine-tuning, RL, evals, or agents scaffolds) and wants to focus on measuring and understanding recursive-self-improvement. You know what the model-development loop looks like from the inside: which signals matter and where the real bottlenecks are. On this team you'll use that judgment to decide what's worth measuring, design the evaluations and models that measure it, and interpret what the results mean for how fast this is moving.</p> <p>&nbsp;</p> <p>We're hiring at both junior and senior levels. Senior researchers should be comfortable doing hands-on technical work alongside setting research direction.</p> <h2>Responsibilities</h2> <ul> <li> <p>Identify the signals that track AI R&amp;D acceleration and design the evaluations that measure them</p> </li> <li> <p>Build quantitative models of capability growth and self-improvement dynamics, grounded in evaluation and telemetry data</p> </li> <li> <p>Run experiments and evals to test hypotheses about automation and capability</p> </li> <li> <p>Make opinionated research bets and own the outcome</p> </li> <li> <p>Write graded assessments of what our measurements show, for internal decision-makers and public reporting</p> </li> <li> <p>Collaborate with pretraining, RL, economic research, and policy teams</p> </li> </ul> <h2>You may be a good fit if you</h2> <ul> <li> <p>Have done hands-on research on large language models: pretraining, fine-tuning, RL, evals, or agent systems</p> </li> <li> <p>Have