Complete real-time patient context from every source that matters - transformed into relevant intelligence for your care teams and their AI agents. Backed by Y Combinator.
About the role
This is the first Machine Learning Engineer role at Metriport. We have access to the richest clinical datasets in the country — longitudinal medical records for hundreds of millions of individuals — and we've barely scratched the surface of what can be learned from it. You'll own machine learning at Metriport end-to-end: from framing the problem with customers, to training the models, to serving them in production and keeping them honest.
What they're looking for
- 7+ years building ML systems that run against real data at scale
- Strong grounding across the ML spectrum: regression and tree-based methods, feature engineering and dimensionality reduction, and deep learning. You've built and trained models yourself, not just orchestrated APIs
- A track record of ML delivering measurable results in production
- Strong software engineering fundamentals: you've built or operated large-scale backend systems on the cloud (ideally AWS) and can own training pipelines, model serving, and monitoring end-to-end
- Strong data skills: SQL, working with large datasets, and building the pipelines that feed your models
- You're located in San Francisco or the Bay Area (or willing to relocate)
More about this role
Medical data exchange is one of the biggest unsolved problems in US healthcare. If you've spent any real time in the healthcare system, you've felt it, and it only gets worse the sicker and older you get. Metriport exists to fix that. We connect to the data sources the healthcare providers of tomorrow need, take raw data that's unusable in its source form, and turn it into a single clean format that care teams, and their agents, actually use to improve outcomes. Record retrieval across thousands of legacy systems and antiquated data pipes that used to take weeks now takes seconds. Clinicians walk into appointments with the full patient picture already in hand, and that speed can mean spotting a condition early enough to actually treat it.
We're not a healthcare company. We're a technology company that happens to operate in healthcare, and we build every layer ourselves: connect, transform, and insight. Legacy EHRs were built to get providers paid, not to serve the clinical experience. We're building what should have existed instead: the system of record for all of US healthcare. We started in data exchange. Today we compete with the largest data platforms in the space. Tomorrow we...
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