Staff Applied Scientist, Hippocratic AI

• 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

Desirable

• 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