Founding Machine Learning Research Engineer (Evaluation & Model Iteration Focus) Location: Bay Area
Onsite
We’re working with a pioneering stealth-stage company in the Bay Area that is redefining how AI is evaluated in healthcare. Most medical imaging AI models today fail in real-world hospital settings because they aren’t rigorously validated. This company is building the evidence infrastructure to change that, tracking model behavior end-to-end, from early development to FDA submission and beyond, so AI systems are reliable, continuously evaluated, and focused on patient outcomes.
Founded by ex-Stanford AI Lab researchers, ex-AWS, with deep expertise in representation learning and working on LLM interpretability.
We are looking for a Founding ML Engineer to:
- Lead investigations into model behavior, failure modes, and uncertainty
- Deliver decision-grade evidence that informs FDA submissions and hospital adoption
- Work directly with medical imaging vendors and hospitals
- Combine hands-on ML skills with strong customer-facing judgment
To succeed in this role, we're looking for a genuine interest in rigorous evaluation/testing of ML systems, especially in medical AI.
This is a high-impact, high-ownership role, your work will directly influence real-world outcomes, FDA approvals, and how high-stakes AI is governed.
Compensation includes competitive salary $200k - $250k + meaningful early-stage equity (1–3%).
If this sounds like something you’d be excited about, please apply with your resume and we can set up a quick conversation to share more details.
