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# Staff Applied Scientist, Reinforcement Learning

- **Company:** Hippocratic AI
- **Location:** Menlo Park, CA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Python (Programming Language), Node.Js, Reinforcement Learning, Pytorch, Large Language Models, Software Coding
- **Published:** July 30, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=7db33aa4a9ccb2f1

## About the Role

* MS or PhD in CS or relevant field
 * 5+ years or experience in NLP, LLM training, or RL
 * 2+ years experience in RL for LLM post-training
 * Experience with large-scale (50B+ parameter and multi-node) LLM training
 * Strong Python and PyTorch coding skills
 * Experience with RLHF, RLVR, LLM-as-judge or similar methods for LLM post-training

Nice-to-Have:

 * Publications at top venues (NeurIPS, ICML, ICLR, ACL, EMNLP)
 * Healthcare domain experience

## Description

LLM post-training is where raw capability becomes reliable, safe behavior - and in healthcare, the stakes are as high as they get. You'll own the Reinforcement Learning (RL) and On-Policy Distillation (OPD) post-training pipeline end to end, to improve our models' clinical reasoning, safety, and alignment. Your models will be deployed to interact with millions of patients across diverse clinical use cases., * Design RL and OPD post-training methods (RLHF, RLVR, OPD, etc.)

 * Build and evaluate reward models, verifiers, and LLM-as-judge pipelines
 * Develop conversational AI environments and simulations for healthcare RL training with synthetic data
 * Automate post-training loops with agents (auto-research)
 * Run rigorous experiments to understand what drives post-training gains
 * Collaborate with research, engineering, and clinical teams


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