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Sprinter Health is reimagining home-based healthcare delivery, operating in 22 states with 2M+ patients served and $125M+ in funding from top-tier investors (a16z, General Catalyst, Accel, GV). The company addresses a critical gap: nearly 30% of U.S. patients skip preventive or chronic care due to access barriers, driving $300B in avoidable annual costs. Sprinter brings care directly to patients' homes using marketplace and last-mile logistics technologies.
As an ML Engineer, you will own the production systems that train, deploy, monitor, and serve machine-learning models reliably. You sit at the intersection of software engineering, data engineering, and data science—translating prototype models into robust, production-grade systems that clinicians and partners depend on.
Key responsibilities include: building and hardening training pipelines; packaging models for deployment; serving predictions via APIs and batch jobs; maintaining feature pipelines; monitoring for drift, data quality, latency, and performance; automating retraining and validation with safe rollback mechanisms; preventing training-serving skew and silent model degradation; productionizing models from other teams; and establishing clean interfaces between data, model, and product systems.
You bring strong Python and software-engineering fundamentals, hands-on experience with ML frameworks, data pipelines, and model serving, and a track record of taking models from prototype to reliable production. You're comfortable with cloud infrastructure, containers, CI/CD, orchestration, monitoring, observability, reproducibility, and versioning. You understand security and privacy controls for sensitive data.
Ideal candidates have backgrounds in backend engineering, data engineering, MLOps, or platform engineering; experience with feature stores or feature pipelines at scale; and familiarity with healthcare data and PHI-aware systems.
The role is hybrid: Monday–Thursday in-office in San Francisco, Fridays work-from-anywhere. The team prioritizes work-life balance, provides daily lunch, and maintains a collaborative culture with board games and team connection time.
