Member of Technical Staff, Reinforcement Learning

About the Role

Join a healthtech team developing clinical decision-support tools for use in healthcare settings. In this hands-on research role, you will build reinforcement learning environments and evaluations that help model-training teams improve clinical reasoning, with a focus on safe, measurable performance.

What You'll Do

• Design and build reinforcement learning environments for complex clinical reasoning, including multi-step tasks, tool use, state transitions, and measurable outcomes.

• Create 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 implementation, evaluation, and delivery to model-training teams.

• Run post-training and agent-evaluation experiments, then use observed failures to improve the environments.

• Collaborate with clinicians and technical leadership to validate model outputs and guide the work.

What We're Looking For

• A PhD in computer science, machine learning, or a related field, or at least three years of full-time experience in reinforcement learning research or post-training.

• At least three years of research or industry experience, or current final-year PhD or postdoctoral status, and a bachelor's degree or higher in a relevant technical field.

• Hands-on experience building RL environments for post-training or agent evaluation, including ownership of reward functions, grading rubrics, or LLM-judge calibration.

• Production-level Python, PyTorch, and Transformers ecosystem skills, with experience in LLMs, reinforcement learning, post-training, evaluation, or reward modeling.

• Experience in clinical AI or clinical reasoning is useful. Familiarity with information retrieval, constraint solving, SAT/SMT, or domain-specific languages is also relevant.

• Clear technical writing about failed experiments and uncertainty, sound judgment when validating model outputs, and comfort with ambiguity and cross-disciplinary work.

• Authorization to work in the United States or Canada for a remote role, and willingness to attend in-person offsites several times per year.

Compensation & Benefits

Base salary: $250,000 to $400,000 USD annually. Visa sponsorship is not available.

Location

Remote, with the primary location in Canada. Candidates must be authorized to work in the United States or Canada.