The opportunity
Anthropic's RL Scaling Science team studies how reinforcement learning behaves as we scale it (across model size, compute, and task horizon) and turns that understanding into the training recipes behind our frontier models. As a Research Engineer on this team, you'll design and…
What you'll do
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
What they're looking for
- 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
