Building AI clinical documentation tools used across 40% of US cancer care.
AI Engineer
Clinicians spend roughly two hours on administrative tasks for every hour of direct patient care. We need an engineer who can pull that burden off their shoulders. You will architect and deploy full-stack machine learning systems—from Python backend pipelines to TypeScript front-ends driven by large language models—that transform ambient conversation into structured medical records. The architecture has to hold up under the strict compliance and reliability demands of real oncology workflows.
What they're looking for
- 2-6 years of software or ML engineering experience shipping production code.
- Fluency in Python and TypeScript, comfortable operating across the stack.
- Demonstrated experience integrating with OpenAI models or similar LLM APIs.
- A pragmatic approach to AI engineering, prioritizing reliable outputs over novelty.
- Ability to work in a hybrid or remote capacity, with optional on-site presence in San Francisco.