Machine Learning Engineer
Sprinter Health
San Francisco, CAOn-siteFull-time$140k – $200k / year
About this role
Machine Learning Engineer @ Sprinter Health
- Back to Sprinter Health’s Job Listings
Machine Learning Engineer
Location
San Francisco, CA
Address
394 Pacific Avenue , San Francisco, California, 94111
Employment Type
Full time
Location Type
Hybrid
Department
Sprinter HealthEngineering
Compensation
- SF Bay AreaEstimated Base Salary $140K – $200K • Offers Equity
About Sprinter Health:
At Sprinter Health, our mission is reimagining how people access care by bringing it directly to their homes. Nearly 30% of patients in the U.S. skip preventive or chronic care simply because they can’t get to a doctor’s office. For many, the ER becomes their first touchpoint with the healthcare system—driving over $300B in avoidable costs every year.
By using the same technologies that power leading marketplace and last-mile platforms, we deliver care where people are, especially those who need it most. So far, we’ve supported more than 2 million patients across 22 states, completed 130,000+ in-home visits, and maintained a 92 NPS. Our team of clinicians, technologists, and operators have raised over $125M to date investors like a16z, General Catalyst, GV, and Accel and enjoy multi-year runway.
About the Role
We’re looking for an ML Engineer to build the production systems that train, deploy, monitor, retrain, and serve our machine-learning models reliably. You sit between software engineering, data engineering, and modeling, and you make ML work in the real world and stay working.
You will build training and inference pipelines, serve predictions through APIs and batch jobs, and stand up the monitoring that catches drift and silent degradation before they reach a patient or a partner. You will turn the models that scientists prototype into systems the company can depend on.
The ideal candidate thinks in systems rather than notebooks, knows what a model needs to become production-ready, and builds clean interfaces between data, models, and produc