Senior Machine Learning Engineer

About Us Hippocratic AI is the leading generative AI company in healthcare. We have the only system that can have safe, autonomous, clinical conversations with patients. We have trained our own LLMs as part of our Polaris constellation, resulting in a system with over 99.9% accuracy. Why Join Our Team Reinvent healthcare with AI that puts safety first. We’re building the world’s first healthcare‑only, safety‑focused LLM — a breakthrough platform designed to transform patient outcomes at a global scale. This is category creation. Work with the people shaping the future. Hippocratic AI was co‑founded by CEO Munjal Shah and a team of physicians, hospital leaders, AI pioneers, and researchers from institutions like El Camino Health, Johns Hopkins, Washington University in St. Louis, Stanford, Google, Meta, Microsoft, and NVIDIA. Backed by the world’s leading healthcare and AI investors. We recently raised a $126M Series C at a $3.5B valuation, led by Avenir Growth, bringing total funding to $404M with participation from CapitalG, General Catalyst, a16z, Kleiner Perkins, Premji Invest, UHS, Cincinnati Children’s, WellSpan Health, John Doerr, Rick Klausner, and others. Build alongside the best in healthcare and AI. Join experts who’ve spent their careers improving care, advancing science, and building world‑changing technologies — ensuring our platform is powerful, trusted, and truly transformative. Location Requirement We believe the best ideas happen together. To support fast collaboration and a strong team culture, this role is expected to be in our Palo Alto office five days a week, unless otherwise specified. About the Role Evaluation is the bottleneck in healthcare AI — you can't ship what you can't measure. You'll build the systems that tell us whether our models are safe, accurate, and ready for real patients: evaluation frameworks, synthetic data pipelines, automated benchmarks, and LLM-as-judge systems. This is a high-leverage engineering role where your work directly gates what goes to production. What You’ll Do Design and build evaluation frameworks for LLM safety, clinical accuracy, and conversational quality Develop synthetic data generation pipelines to stress-test models across diverse clinical scenarios Build automated and human‑in‑the‑loop evaluation pipelines at scale Create benchmarks, metrics, and LLM‑as‑judge systems for healthcare tasks and conversational experience Analyze failure modes and translate findings into actionable model improvements by collaborating with the LLM post‑training team Collaborate with research, engineering, and clinical teams to define and raise the quality bar What You Bring Must‑Have MS or PhD in CS or related field 5+ years in ML engineering, evaluation systems, or applied ML Strong software engineering skills — Python, PyTorch, and production‑quality code Hands‑on experience with LLM evaluation, benchmarking, or synthetic data generation Comfort building robust data analysis and evaluation infrastructure, not just running experiments Experience with UI/UX and front‑end development toolkits such as Streamlit, Gradio, React, etc. Nice‑to‑Have Experience in healthcare AI Experience with RL/RLVR/RLHF or safety evaluation #J-18808-Ljbffr