Anthropic· AI Research & Engineering· Remote-Friendly (Travel Required) | San Francisco, CA; San Francisco, CA | New York City, NY
Research Lead, Training Insights
Classified Tasks (17)
Automate 0%Augment 59%Human-Only 41%
Augment (10)
AI assists, human decides
Lead execution of measurement and characterization efforts for model capabilities across training and deployment
leadership
Research and build novel long-horizon evaluations for models
technical
Develop novel measurement approaches to understand how model capabilities emerge and evolve during RL training
analytical
Analyze how model capabilities develop during production reinforcement learning training and after deployment
analytical
Map the landscape of model evaluations across Reinforcement Learning, Pretraining, Inference, Product, Alignment, Safeguards, and other teams
operational
Identify critical gaps in evaluation coverage across the organization
analytical
Contribute to communications about model evaluation results to internal and external audiences
communication
Design evaluation frameworks that balance scientific rigor with the practical demands of production training schedules
technical
Ensure evaluation insights inform deployment decisions
operational
Contribute to the broader research community through publications, open-source contributions, or external engagement on evaluation best practices
communication
Human-Only (7)
Requires human judgment
Develop the strategy for how Anthropic measures and characterizes model capabilities across training and deployment
leadership
Drive original research into new evaluation methodologies for models
technical
Lead and mentor a small team of researchers and research engineers, setting research direction
leadership
Lead strategic evaluation coverage across the company
leadership
Shape the evaluation narrative for model releases
communication
Build and maintain relationships across Anthropic's research organization to ensure evaluation insights inform training decisions
communication
Set research priorities and direction for evaluation projects and experiments
leadership
Job description
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 Research Lead on the Training Insights team, you'll develop the strategy for, and lead execution on, how we measure and characterize model capabilities across training and deployment. This is a hands-on leadership role: you'll drive original research into new evaluation methodologies while leading a small team of researchers and research engineers doing the same. Your work will span the full lifecycle of model development. You'll research and build new long-horizon evaluations that test the boundaries of what our models can achieve, develop novel approaches to measuring emerging capabilities, and deepen our understanding of how those capabilities develop — both during production RL training and after. You'll also take a cross-organizational view, working across Reinforcement Learning, Pretraining, Inference, Product, Alignment, Safeguards, and other teams to map the landscape of model evaluations at Anthropic and identify critical gaps in coverage. This role carries significant visibility and impact. You'll help shape the evaluation narrative for model releases, contributing directly to how Anthropic communicates about its models to both internal and external audiences. Done well, you will change how the industry measures and understands model capabilities, significantly furthering our safety mission. Responsibilities: Build new novel and long-horizon evaluations Develop novel measurement approaches for understanding how model capabilities emerge and evolve during RL training Lead strategic evaluation coverage across the company Shape the evaluation narrative for model releases Lead and mentor a small team of researchers and research engineers, setting research direction and fostering a culture of rigorous, creative research Design evaluation frameworks that balance scientific rigor with the practical demands of production training schedules Build and maintain relationships across Anthropic's research organization to ensure evaluation insights inform training and deployment decisions Contribute to the broader research community through publications, open-source contributions, or external engagement on evaluation best practices You may be a good fit if you: Have significant experience designing and running evaluations for large language models or similar complex ML systems Have led technical projects or teams, either formally or through sustained ownership of critical research directions Are equally comfortable designing experiments and writing code—you can move between research and implementation fluidly Think strategically about what to measure and why, not just how to measure it Can synthesize information across multiple teams and workstreams to form a coherent picture of model capabilities Communicate complex technical findings clearly to both technical and non-technical audiences Are results-oriented and thrive in fast-paced environments where priorities shift based on research findings Care deeply about AI safety and want your work to directly influence how capable AI systems are developed and deployed Strong candidates may also have: Experience building evaluations for long-horizon or agentic tasks Deep familiarity with Reinforcement Learning training dynamics and how model