Member of Technical Staff, Reinforcement Learning

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.

• 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.

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

• 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.

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