RL Researcher: Build Self-Improving Medicine Environments

Endo Health, Inc.; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Endo Health, Inc. is seeking a researcher to build the RL environment for self-improving medicine in a clinical setting. You will design branching care journeys, partial observations, and delayed outcomes to enable robust learning loops that improve patient care over time.

You’ll work with engineers and clinicians to define the problem, develop learning strategies, and validate improvements with unseen cases. San Francisco relocation support is offered.

Qualifications

• You've built and debugged training experiments yourself.
• You have depth in RL, post-training, or sequential decision-making.
• You can explain why a result is real, where it breaks, and what to test next.
• Shape the research agenda. Own the connection between the environment, objectives, training, and evaluation.

Responsibilities

• Build the environment: branching care journeys, tools, partial information, and delayed outcomes.
• Build the learning loop: demonstrations, reward design, post-training, and reproducible experiments.
• Prove improvement: beat baselines on unseen cases and catch reward hacking, leakage, and simulator shortcuts.

Skills

Reinforcement Learning

Job description

Endo Health, Inc. is seeking a researcher to build the RL environment for self-improving medicine in a clinical setting. You will design branching care journeys, partial observations, and delayed outcomes to enable robust learning loops that improve patient care over time.

You’ll work with engineers and clinicians to define the problem, develop learning strategies, and validate improvements with unseen cases. San Francisco relocation support is offered.