Sprinter Health
Machine Learning Engineer
$140K–$200K
San Francisco, CA · Hybrid · Full-time · Posted Jul 27, 2026
About the job
Build and operate production machine-learning systems that train, deploy, serve, monitor, and retrain models reliably.
What you'll do
- Build training and feature pipelines; package models and serve predictions through APIs or batch jobs.
- Monitor model and system reliability, including drift, data quality, latency, cost, and performance; automate retraining, validation, and rollback.
- Productionize models and create clean interfaces across data, model, and product systems, with reproducibility, versioning, and governance artifacts.
What they ask for
- Strong Python and software-engineering fundamentals.
- Experience with ML frameworks, data pipelines, and model serving.
- Experience taking models from prototype to reliable production.
- Experience with cloud infrastructure, containers, CI/CD, orchestration, monitoring, observability, reproducibility, versioning, and security and privacy controls for sensitive data.
Nice to have
- Background in backend engineering, data engineering, MLOps, or platform engineering; experience with feature stores or feature pipelines at scale.
- Familiarity with healthcare data and PHI-aware systems.
Pay
$140K – $200K USD base salary
Tools
Python
AI focus
Productionize and operate machine-learning models, including training, inference, monitoring, and retraining.
Model-written summary · the original posting is authoritative