Research Engineer, RL Scaling Science

• Join the RL Scaling Science team studying how reinforcement learning behaves as it scales across model size, compute, and task horizon, turning that understanding into the training recipes behind Anthropic's frontier models. • Design and run large-scale experiments to understand and resolve bottlenecks, build benchmarks that make long-horizon progress measurable, and ship validated findings directly into production training. • Work at the boundary between research and engineering where the problems are open, the experiments run at frontier scale, and the path from a robust result to production is short.

• Have strong empirical research skills in Reinforcement Learning, large-scale ML training, or a closely adjacent area. • Have demonstrated ability to own large experiments end-to-end from design through interpretation. • Be proficient in Python and have experience working with large-scale or distributed ML systems. • Be comfortable operating at the research/systems boundary including debugging where the two meet. • Care about the societal impacts of AI and responsible scaling.

• Have published or shipped work in long-horizon RL or RL fundamentals. • Have experience translating research findings into production training recipes. • Have demonstrated large-scale industry impact via RL interventions. • Have experience working on frontier-scale training runs with long trajectories.

• Design, run, and interpret large-scale RL experiments, reasoning rigorously about what the data does and does not show. • Investigate how RL improves as horizon, compute, and model size grow. • Build and maintain benchmarks for long-horizon RL so progress is measurable and reproducible. • Translate validated findings into production training recipes, exercising judgement about when a result is robust enough to ship. • Debug complex issues at the seam where research meets infrastructure, addressing failures that only appear at scale. • Partner closely with adjacent RL teams across research and engineering and advance the overall RL stack.

• Receive an annual salary of £375k–£640k GBP. • Work from the London office with a hybrid policy requiring at least 25% office time. • Receive visa sponsorship with every reasonable effort made and an immigration lawyer retained to help. • Receive competitive compensation and benefits with optional equity donation matching. • Receive generous vacation and parental leave. • Enjoy flexible working hours.

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The company is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Anthropic is a public benefit corporation headquartered in San Francisco with offices in London.