The posting
Head of Reinforcement Learning (RL) Operations About the Role Hippocratic AI is building safety-focused generative AI for healthcare, deployed at scale across health systems, payors, and pharma. We are a technology and product company, and the quality of our models depends on the quality of the human expertise and data that train and evaluate them. Hippocratic AI is making a significant, multi-year investment in RL infrastructure, one of the largest commitments in the company’s history. We have made real progress on the technology and are now scaling the operation behind it. We are hiring a Head of RL, a newly created senior leadership role, to build and run that operation end to end. We are building this capability in-house. Data labeling has changed dramatically as LLMs have advanced. Today it is complex, expert-driven work that spans software interfaces, platforms, and in some cases training models directly. This role is for a leader who has already built an operation like this at scale, was there through the build-out phase, and can do it again here.
What You'll Own RL Operations, End to End Own the full RL operation: strategy, design, execution, quality, throughput, and cost. Translate the needs of our research and engineering teams into well-run programs that deliver high-quality data and signal on schedule, and build the operating cadence, metrics, and reporting that leadership and the board rely on.
Team Build-Out Build and lead the team, starting at roughly ten people with four to five direct reports from day one and growing substantially as the program scales. Hire senior leaders, set the structure and operating model, and create a culture of rigor and ownership.
Expert Labeler Network We have already built a gig-economy network of expert labelers. You will inherit this network as a core resource and be responsible for growing it, managing quality, and deepening domain coverage across clinical and non-clinical specialties.
Platforms and Tooling Drive the build of the software interfaces and platforms that labelers and reviewers work in, partnering closely with Engineering. Define product requirements based on how complex annotation and RL workflows actually run, and push for tooling that improves quality and efficiency.
Model Training Take an active role in training some of our models directly, working hand in hand with Research to turn operational data into model improvements and to close the loop between labeling, evaluation, and training.
Scaling to a Very Large Program Plan and execute the growth of the program to a very large scale, including capacity planning, budget ownership, in-house sourcing and onboarding of talent, and the systems needed to maintain quality as volume grows.
What You Bring
● Bachelor's degree in Computer Science, Machine Learning, or a related field
● A track record of building and scaling a large RL, data, or human-feedback operation. Scale of operations, scope of impact, and depth of knowledge matter more to us than years of experience or company size.
● Experience as a VP, SVP, or equivalent senior leader at a data-labeling company, a hyperscaler, or a frontier model lab. If you come from a labeling company, operations with tens of millions of dollars in revenue or comparable scale.
● Presence through a build-out phase: you have taken a function from early stage to a large, mature operation, not only run one that already existed.
● Deep understanding of modern LLM labeling and RL workflows, including expert annotation, quality control, evaluation, and how human feedback translates into model gains.
● Ability to manage complex, multi-faceted operations end to end, spanning people, process, tooling, and models.
● Strong technical fluency and credibility with Research and Engineering teams, with experience shaping internal software platforms.
● Proven ability to recruit, develop, and lead senior managers and large distributed workforces, including contractor and gig-based expert networks.
● Strong judgment, financial discipline, and executive communication. Comfortable owning a large budget and reporting to senior leadership and the board.
● Willingness to work on-site five days a week in Menlo Park, CA; local candidates preferred.
Nice to Have
● Experience training or fine-tuning models directly, including RLHF, RLAIF, or reward modeling.
● Experience managing clinical or other highly credentialed expert labeler populations.
● Background in healthcare, regulated industries, or safety-critical AI.
Why Hippocratic AI We are an actual technology company building AI that touches patient lives, which means our bar for safety and quality is not a checkbox. It is the foundation of everything we ship. This is a rare chance to build a major, board-backed operation from the ground up, with the resources, mandate, and existing expert network to move quickly, and to shape how safe, reliable healthcare AI is trained.
Why Join Hippocratic AI
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.
Equal Opportunity
Hippocratic AI is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, national origin, sex, age, disability, sexual orientation, gender identity or expression, genetic information, military or veteran status, or any other characteristic protected by applicable law. We are committed to building a team that reflects the patients we serve. We actively encourage applications from candidates of all backgrounds. If you require accommodations during the hiring process, please contact [email protected].
Please be aware of recruitment scams impersonating Hippocratic AI. All recruiting communication will come from @hippocraticai.com email addresses. We will never request payment or sensitive personal information during the hiring process.
