Senior Applied Scientist, Reinforcement Learning

Hippocratic AI • Menlo Park, CA

3d • Onsite

About The Position

Hippocratic AI is seeking a Senior Applied Scientist to own the Reinforcement Learning (RL) and On-Policy Distillation (OPD) post-training pipeline end to end. The role focuses on improving the clinical reasoning, safety, and alignment of the company’s models, which are deployed to interact with patients across diverse clinical use cases. The position is expected to be performed in the Menlo Park office five days a week, unless otherwise specified.

Requirements

• MS or PhD in computer science or a relevant field.
• 3+ years of experience in NLP, LLM training, or RL.
• 1+ year of experience in RL for LLM post-training.
• Experience with large-scale LLM training involving 50B+ parameters and multiple nodes.
• Strong Python and PyTorch coding skills.
• Experience with RLHF, RLVR, LLM-as-judge, or similar LLM post-training methods.

Responsibilities

• Design RL and OPD post-training methods, including RLHF, RLVR, and OPD.
• Build and evaluate reward models, verifiers, and LLM-as-judge pipelines.
• Develop conversational AI environments and healthcare simulations for RL training using synthetic data.
• Automate post-training loops with agents for auto-research.
• Run rigorous experiments to understand the drivers of post-training gains.
• Collaborate with research, engineering, and clinical teams.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior