Research Scientist, Science of Post-Training and Reinforcement Learning

You will work closely with Ian Osband and the team on research around post-training for agents and LLMs, including practical RL methods and evaluation. This is not a theory-only role; you should expect to implement code, run experiments, and own results end-to-end. Success in this role is defined by whether the team learns faster and whether the work produced is crisp, honest, and high-quality.

Key Responsibilities

• Propose and test research hypotheses in post-training and RL for agents/LLMs.

• Implement algorithm ideas and run end-to-end experiments, including setup, execution, analysis, and iteration.

• Design evaluations and ablations that answer real questions and change minds.

• Analyze results carefully,  including debugging and failure analysis.

• Communicate clearly through plots, writeups, and paper-ready narratives and figures.

• Collaborate closely with engineering and research partners to keep the team aligned on findings and strategy.

• Contribute to a culture of first-principles thinking, high standards, and direct, constructive feedback.

• A research track record in ML/RL, demonstrated through publications or high-quality projects.

• Strong implementation ability and comfort working in research codebases.

• Evidence of owning experiments end-to-end, including analysis and interpretation.

• Strong communication skills and a bias toward clarity and honesty regarding results.

• High agency and drive: You push projects forward, prioritize effectively, and take initiative.

• PhD in ML preferred, or equivalent practical experience.

• Experience with RL for sequence models, post-training, preference-based learning, or agentic systems.

• Experience with modern research stacks (e.g., JAX/Flax or PyTorch) and scaling experiments.

• Strong experimental taste: Good judgment regarding baselines, ablations, and what is worth testing.

• Comfort with scaling, evaluation methodologies, and diagnosing complex failure modes.

• A focus on craft: You care about doing excellent work while maintaining a high velocity.