Staff Applied Scientist, Reinforcement Learning

About the job

Role mission

As HAI's LLM Post-Training Staff Applied Scientist, you will own the reinforcement learning and on-policy distillation pipeline that transforms raw model capability into reliable, safe clinical behavior. Your post-training methods will directly determine how our AI agents reason through complex clinical scenarios, handle safety-critical decisions, and ultimately impact millions of patient interactions. This role exists because post-training is where capability becomes trustworthiness—and in healthcare, that's everything.

What you will accomplish

Own your first major outcome: By day 90, you will have shipped a post-training improvement that meaningfully advances model performance on a critical clinical capability (clinical reasoning, safety alignment, or task completion), evaluated the gains rigorously, and contributed that learning to our post-training roadmap.

Drive lasting impact: At 12 months, you will have designed and shipped multiple post-training methods that measurably improve our models' clinical safety and reasoning, built reusable infrastructure (reward models, verifiers, evaluation frameworks) that accelerate future post-training work, published your research or contributed to HAI's intellectual property, and directly shaped how our deployed models behave in production healthcare environments.