
Job Overview
Location
Palo Alto
Job Type
Full-time
Category
Data Science
Date Posted
April 7, 2026
Full Job Description
📋 Description
- • Senior Applied Scientist role focused on owning the RL-based post-training pipeline end-to-end to improve clinical reasoning, safety, and alignment of Hippocratic AI’s healthcare-specific LLMs, directly impacting patient outcomes at global scale.
- • Day-to-day responsibilities include designing and iterating on RL-based post-training methods (RLHF, RLVR, DPO), building and evaluating reward models and verifiers, developing conversational AI environments for healthcare RL training with synthetic data, running rigorous experiments to understand post-training gains, and collaborating with research, engineering, and clinical teams.
- • Hippocratic AI is the leading generative AI company in healthcare, backed by $404M in funding and a $3.5B valuation, building the world’s first healthcare-only, safety-focused LLM with over 99.9% accuracy, co-founded by physicians, AI pioneers, and researchers from top institutions including Stanford, Google, Meta, Microsoft, and NVIDIA.
- • The role offers the opportunity to work at the forefront of AI in healthcare, contribute to category-defining technology, learn from world-class experts in both AI and clinical care, and ensure models are safe, trusted, and transformative for millions of patient interactions.
Skills & Technologies
About Hippocratic AI Inc.
Hippocratic AI develops safety-focused large language models specifically for healthcare. Its non-diagnostic generative AI handles patient-facing tasks such as chronic care check-ins, medication adherence calls, appointment scheduling, and post-discharge follow-up, operating under evidence-based clinical safeguards and regulatory-grade risk management. The company trains models on peer-reviewed literature, clinical guidelines, and simulated patient conversations, then validates them with licensed clinicians. Founded in 2022 and headquartered in Palo Alto, California, Hippocratic AI partners with health systems, payers, and digital health companies to reduce staffing shortages and improve access to care without compromising patient safety or privacy.
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