Senior MLOps Engineer
Core
Design and evolve platforms, workflows, and governance practices enabling ML teams to develop, train, deploy, and operate ML systems reliably at scale.
Role type
Senior MLOps Engineer (Platform & Enablement)
Builds
Shared cloud and data platform ecosystem for ML workflows, training orchestration, and deployment pipelines.
Domain
Health technology / Machine Learning Operations
Deliverable
production ML models | infrastructure
Required skills
MLOps, cloud infrastructure (AWS), ML lifecycle management, workflow orchestration, infrastructure-as-code, CI/CD, model governance, experiment tracking (MLflow), cross-team collaboration
Preferred skills
Databricks, shared MLOps platforms for multiple DS teams, governance controls at scale, high-growth environment experience
Technologies
AWS, MLflow, Databricks
Responsibilities
Lead development of environment and platform capabilities supporting ML workflows; Drive design and unification of workflows for reliable training, orchestration, and deployment; Partner with data scientists to improve end-to-end ML lifecycle; Define and evolve model governance practices including reproducibility and access controls; Standardize ML tooling and workflows; Identify and resolve reliability, scalability, and cost-efficiency issues in ML infrastructure; Drive standards, automation, and documentation for ML development.
Seniority
Senior, hands-on IC with cross-team leadership
