Senior Machine Learning Operations Engineer
Garner Health is seeking a Senior Machine Learning Operations Engineer to join their Platform Engineering team in New York City. This role focuses on building and operating production machine learning systems that power Garner's healthcare products, ensuring secure and consistent model deployment. As an early member of the MLOps function, the engineer will collaborate closely with machine learning and data science teams to maintain high standards of production quality, directly impacting health outcomes and cost-effectiveness for millions of patients.
The Senior MLOps Engineer will be responsible for ensuring the reliability, performance, functionality, and cost-efficiency of Garner's production ML systems. Key tasks include building components of the ML platform such as feature stores, model registries, and CI/CD pipelines, transitioning deployment processes to automated, PR-driven workflows with data quality checks and statistical model validation. The role also involves optimizing architecture, hardware, and models to reduce costs and latency, contributing to MLOps workflows, standards, and KPIs, and establishing automated data drift and concept drift monitoring systems.
Candidates should have over five years of software engineering experience, particularly in operating ML or data-intensive systems in production. Hands-on experience with modern ML production stacks, including model serving (e.g., Sagemaker, Triton), feature stores, model registries, and CI/CD for ML, is essential. Strong infrastructure and platform engineering skills are required, encompassing Kubernetes, containerization, cloud services (preferably AWS), Terraform/IaC, observability, and incident response. Experience in building ML platforms or significant components thereof, with sound judgment on when to build versus buy, is important. The role demands strong collaboration with ML, data, platform engineers, data scientists, and product engineering teams, with the ability to lead projects and influence technical decisions. Experience in healthcare, regulated data, or high-stakes production ML is a plus but not mandatory. A desire to be part of a high-performing, mission-driven team that operates with urgency, accountability, and a commitment to authentic feedback is crucial.
The target salary range for this position is $256,000 to $285,000 annually. In addition to base compensation, the role offers participation in equity incentives and competitive benefits, including flexible paid time off, medical, dental, and vision plan options, a 401(k) plan, and Teladoc Health services.
Garner Health is a rapidly growing healthcare technology company committed to transforming the healthcare economy by delivering high-quality and affordable care. The company partners with employers to redesign healthcare benefits using clear incentives and data-driven insights, guiding employees to higher-quality, lower-cost care. Garner's products are trusted by sophisticated employers and providers, and the company is building a team of talented, mission-driven individuals motivated to make a meaningful impact on healthcare at scale.