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Garner Health is seeking a Staff Machine Learning Operations Engineer to join the Platform Engineering team, reporting to the VP of Platform Engineering. This is Garner's foundational dedicated MLOps role, responsible for the reliability, performance, and cost-efficiency of production machine learning systems that directly influence health outcomes for millions of patients.
Key responsibilities include:
- Own reliability, performance, functionality, and cost-efficiency of production ML systems, establishing SLOs, observability, and on-call responsibilities
- Architect Garner's ML platform including data infrastructure (feature store, model registry, CI/CD for models) and standardized service patterns
- Implement ML-specific CI/CD pipelines, transitioning from manual notebook hand-offs to automated, PR-driven workflows with automated data quality checks and statistical model validation
- Drive down cost and latency through improved architecture, hardware choices, and model optimization
- Lay the foundation for a future MLOps team, including workflows, standards, and KPIs for rapid onboarding and health visibility
- Design and implement automated data drift and concept drift monitoring systems that alert teams when models degrade
Ideal candidates have 7+ years of software engineering experience with significant time operating ML or data-intensive systems in production at scale. Required expertise includes modern ML production stack (model serving, feature stores, model registries, CI/CD for ML), infrastructure and platform engineering fundamentals (Kubernetes, containerization, AWS, Terraform/IaC, observability, incident response), and experience designing ML platforms or significant components. Healthcare or regulated-data production ML experience is a plus.
The role is based in Garner's New York City Financial District office with a hybrid schedule of 3 days per week (Tuesday, Wednesday, Thursday in-office). Garner is a Series E-funded company on a mission to transform the U.S. healthcare system by identifying best-performing doctors and steering members to higher-quality care, resulting in better outcomes and lower costs. The company has helped 2.5M+ people access higher-quality care and saved $1B in healthcare costs in five years.
