Senior Applied Scientist
Hippocratic AI2 months ago
Responsibilities
- Build and maintain reproducible training, evaluation, and deployment loops for the self-improvement system.
- Design and implement reward and feedback signals while investigating reward hacking, specification gaming, and distribution drift.
- Build evaluation harnesses and metrics to measure system improvement and safety.
- Own data pipelines and automated data flywheels that feed the learning loop.
- Debug model-quality regressions and stabilize non-stationary training and feedback loops.
- Collaborate with research and product teams to turn methods into robust, shippable systems.
Requirements
- Strong machine learning engineering fundamentals and excellent Python skills with clean, well-tested ML training code.
- Experience building or owning a feedback loop, reward model, evaluation harness, RLHF/RLAIF or active-learning system, retraining pipeline, continual-learning pipeline, or agentic evaluation harness.
- Understanding of data pipelines, distributed or large-scale training, experiment tracking, and production ML systems.
- Working knowledge of reward modeling, on-policy and off-policy tradeoffs, credit assignment, and feedback-system failure modes.
- Experience shipping an ML system to production and maintaining its health over time.
- PhD or MS in reinforcement learning or machine learning paired with production experience is preferred.
- Experience at a lab or company working on RLHF, agents, or large-scale ML infrastructure is preferred.
- Familiarity with LLM fine-tuning, evaluation frameworks, or agent orchestration is preferred.
Benefits
- Work on a safety-focused healthcare AI platform intended to improve patient outcomes.
- Collaborate with physicians, hospital leaders, AI researchers, and engineers from leading institutions and technology companies.
- Hippocratic AI is an equal opportunity employer and provides accommodations during the hiring process.
Tech Stack
Categories
About Hippocratic AI
Hippocratic AI builds a safety-focused large language model and AI agents for healthcare workflows, used by health systems for patient outreach, post-discharge follow-up, and chronic-care management. It licenses its platform and tools to providers to automate and scale clinical support tasks while meeting health-system requirements. Founded in 2023 and headquartered in Palo Alto, the company is privately held.