Staff ML Engineer

About the Role

Early-stage, well-funded healthcare AI startup focused on reducing waste in the U.S. healthcare system by improving care decisions through data and AI.

Role Overview

Seeking a Staff/Senior AI Engineer to own development of core platform components, including models that assess appropriate patient care. This is a hybrid role in San Francisco (2–3 days/week) with high ownership and cross-functional responsibility (backend + data + ML).

What You’ll Do

• Build LLM/NLU systems to process clinical notes and medical records, and generate care recommendations
• Develop evaluation frameworks, benchmarking, and model governance for reliable AI systems
• Design and scale secure data pipelines handling sensitive healthcare data
• Partner with engineering to integrate ML systems into production applications

Key Technical Challenges

• Extracting and structuring insights from unstructured medical records
• Improving LLM reliability and accuracy for clinical decision support
• Evaluating provider adherence to medical guidelines
• Building explainable AI systems for healthcare use cases

Tech Stack

• AWS (ECS, Bedrock, Cognito), Docker
• Python, Django, Celery
• PostgreSQL (RDS), S3
• Github, CI/CD tools

Requirements

• 5+ years building and deploying production backend/data systems
• Experience developing LLM-based systems for structured + unstructured data
• Strong understanding of LLM limitations and best practices
• Ability to operate in a startup environment with high ownership

Nice to Have

• Experience working with medical records or healthcare data (HIPAA)
• Background in clinical assessments, claims, or care guidelines
• Experience with data pipelines and ML infrastructure (MLOps)
• Generalist engineering background (backend + ML)

Why Join

• High-impact problem in healthcare
• Early-stage ownership + equity
• Work closely with experienced founders
• Hybrid SF with flexible culture