Senior Machine Learning Operations Engineer
Core
Build and operate production machine learning systems, including data infrastructure and CI/CD pipelines, to enable secure and consistent deployment of models that influence health outcomes and cost-effectiveness.
Role type
Senior MLOps Engineer
Builds
Production ML systems, data infrastructure (feature stores, model registries), and automated CI/CD workflows for model deployment.
Domain
Healthcare technology / Machine Learning Operations
Deliverable
infrastructure
Required skills
Kubernetes, containerization, cloud platforms (AWS), Infrastructure as Code (Terraform), observability, incident response, model serving, feature stores, model registries, CI/CD for ML, statistical model validation, data quality checks, model optimization, drift monitoring.
Preferred skills
Healthcare or regulated-data production ML experience, building ML platforms from scratch.
Technologies
Python, Kubernetes, AWS, Sagemaker, Terraform, S3, Snowflake, Airflow, Datadog
Responsibilities
Ensure reliability, performance, functionality, and cost-efficiency of production ML systems; build key components of the ML platform; implement ML-specific CI/CD pipelines; drive down cost and latency through architecture and optimization; establish drift monitoring systems.
Seniority
Senior, hands-on IC
