Anthropic's RL Scaling Science team studies how reinforcement learning behaves as we scale it and turns that understanding into the training recipes behind frontier models. As a Research Engineer on this team, you'll 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.
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
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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