Sprinter Health is seeking a Staff Machine Learning Engineer to build and lead its ML engineering function, designing production systems for training, deploying, and monitoring ML models. This founding role involves defining ML infrastructure strategy, building reliable pipelines, and collaborating with cross-functional teams. The ideal candidate has 8+ years of experience in ML infrastructure and production systems.
Responsibilities
Build and lead Sprinter’s ML engineering function as the company’s first dedicated ML engineering hire.
Define Sprinter’s ML platform and deployment paradigm across training, serving, features, monitoring, retraining, and governance.
Make foundational build-versus-buy, architecture, tooling, and platform decisions that future models and engineers will build on.
Design and build production training and inference pipelines that are reliable, observable, and maintainable.
Package models for deployment and serve predictions through APIs, batch jobs, or other production workflows.
Build clean interfaces between data systems, models, and product systems so ML can be consumed safely and reliably.
Maintain feature pipelines and ensure features remain fresh, correct, and consistent between training and serving.
Implement monitoring for model performance, drift, data quality, latency, cost, reliability, and production behavior.
Prevent training-serving skew, silent degradation, and model regressions before they become production issues.
Sprinter Health is a healthcare technology company that reimagines care at home by combining a full-stack medical practice with proprietary technology. They partner with healthcare organizations to deliver preventive care, diagnostics, and wellness visits through a hybrid model that utilizes in-home clinical staff supported by virtual clinicians.
