Anthropic’s RL Scaling Science team seeks a Research Engineer to design, run, and interpret large‑scale reinforcement learning experiments, build benchmarks for long‑horizon RL, translate findings into production training recipes, debug scale‑specific issues, and collaborate closely with adjacent RL teams.
Research Engineer, RL Scaling Science at Anthropic
Hybrid - London, UK
More jobs at AnthropicSalary
GBP 375,000 - 640,000
Requirements
Skills
- Strong empirical research skills in Reinforcement Learning, large-scale ML training, or a closely adjacent area
- Demonstrated ability to own large experiments end-to-end, from design through interpretation
- Proficiency in Python and experience working with large-scale or distributed ML systems
- Comfort operating at the research/systems boundary, including debugging where the two meet
- Care about the societal impacts of AI and responsible scaling
- Published or shipped work in long-horizon RL or RL fundamentals
- Experience translating research findings into production training recipes
- Demonstrated large scale industry impact via RL interventions
- Experience working on frontier-scale training runs with long trajectories
Responsibilities
- Design, run, and interpret large-scale RL experiments, reasoning rigorously about what the data does and doesn't 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 judgment about when a result is robust enough to ship
- Debug complex issues at the seam where research meets infrastructure - failures that only appear at scale
- Partner closely with adjacent RL teams across research and engineering and advance our overall RL stack
Technologies
PythonReinforcement LearningLarge-scale ML trainingDistributed ML systems
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