reinforcement learning
ABOUT THE ROLE
Join a healthtech team developing validated clinical decision tools for use in healthcare settings. You will build reinforcement learning environments and evaluations that support safer, more reliable clinical AI.
WHAT YOU'LL DO
- Build RL environments for complex clinical reasoning, including multi-step tasks, tool use, state transitions, and measurable outcomes.
- Design and calibrate reward functions, grading rubrics, and LLM judges, and test them for reward hacking and misleading scores.
- Own the workflow from task design and data creation through environment implementation, evaluation, and delivery to model-training teams.
- Run post-training and agent evaluation experiments, then use failures to improve environments.
- Collaborate with researchers and clinicians who validate model outputs.
WHAT WE'RE LOOKING FOR
- A PhD in computer science, machine learning, or a related field, or at least three years of full-time RL research or post-training experience.
- At least three years of research or industry experience, or current status as a final-year PhD student or postdoctoral researcher.
- Hands-on experience building RL environments for post-training or agent evaluation, including experience in a full-time role at a leading AI lab or company.
- Strong technical fundamentals, with a BS or higher in computer science, machine learning, mathematics, or a related field.
- Production-level Python, PyTorch, and Transformers ecosystem experience, plus familiarity with LLMs, reinforcement learning, post-training, evaluation, and reward mo