# Machine Learning Engineer at Hippocratic AI

- Company: Hippocratic AI
- What the company does: Hippocratic AI builds the safest generative AI healthcare agent for health systems, payors, and pharma. Over 180 million clinical interactions across 1,000+ use cases with 60+ partners worldwide. Backed by General Catalyst, Kleiner Perkins and a16z.
- Company website: https://www.hippocraticai.com/
- Type: Startups (AI role)
- Level: Mid level
- Location: Menlo Park, CA
- Work setup: On-site
- Posted: 2026-09-23
- Apply by: 2026-11-07
- Apply: https://jobs.ashbyhq.com/hippocratic%20ai/9d8a02ed-ba1a-4fc0-b5cd-5fdd832a7b04
- Page: https://www.1752.vc/careers/jobs/hippocratic-ai-machine-learning-engineer/

## About the role

We are building a recursive self-improvement system — a machine learning system that iteratively improves itself through feedback, evaluation, and automated learning loops. You will help build the engineering pipeline that keeps these loops fast, reliable, and trustworthy: the training and evaluation pipelines, the reward and feedback signals, and the safeguards that prevent a self-improving system from silently degrading or gaming its objectives.

## What they're looking for

- Built or owned part of a feedback loop — a reward model, an evaluation harness, or the data pipeline for an RLHF/RLAIF or active-learning system
- Ran a retraining or continual-learning pipeline where a model consumed its own predictions or production data (e.g. ranking, recommendations, fraud, spam)
- Fine-tuned LLMs with human or AI feedback, or built agentic evaluation harnesses
- The ideal candidate has built or shipped a full system that improved from its own outputs or feedback end to end. This is rare at this level, so treat it as a standout differentiator rather than a filter. Examples:
- RLHF / RLAIF pipelines
- Self-play systems

Tags: Research & Development