Sprinter Health combines technology and a full-stack medical practice to reimagine care at home. Backed by Accel, General Catalyst and a16z.
About the role
Deciding what Sprinter’s serving and feature paradigms should be and writing the design docs behind those decisions Debugging a model-serving issue or production data quality problem
What they're looking for
- Spent 8+ years building production software, data systems, ML systems, platform infrastructure, or related technical systems
- Built and owned ML systems in production across training, serving, features, monitoring, and deployment
- Taken models from prototype or research stage into reliable, production-grade systems
- Built or meaningfully scaled ML infrastructure, MLOps platforms, model-serving systems, feature pipelines, or related infrastructure
- Designed systems that other engineers, data scientists, analysts, or product teams rely on
- Made architectural decisions around ML platform design, serving patterns, feature infrastructure, build versus buy, and operational standards
More about this role
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 has raised over $125M from investors like a16z, General Catalyst, GV, and Accel and enjoys multi-year runway.
About the Role
We’re looking for a Staff Machine Learning Engineer to be Sprinter’s first dedicated ML engineering hire and build the production systems that train, deploy, monitor, retrain, and serve machine learning models across the company.
This is a founding, first-of-function role. You will define the blueprint for how ML moves from prototype to production at...
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