Machine Learning Ops Engineer
Core
Design, build, and operate infrastructure and tooling for end-to-end ML workflows on AWS to ensure models are reliable, secure, and scalable in production.
Role type
MLOps Engineer
Builds
Production ML services, data pipelines, feature stores, and CI/CD pipelines for ML models.
Domain
Healthcare technology / Cloud Infrastructure
Deliverable
production ML models
Required skills
Python, AWS MLOps services (SageMaker, Bedrock, Snowflake Cortex), CI/CD tools, Infrastructure-as-Code, SQL, Snowflake, Containerization, Event streaming
Preferred skills
Kubernetes, Terraform, HIPAA compliance knowledge
Technologies
AWS (SageMaker, Bedrock, Snowflake, Glue, Lambda, Step Functions, IAM, CloudWatch, ECR, ECS/EKS, S3), Snowflake Cortex, GitHub Actions, GitLab CI, CodePipeline, Terraform, CloudFormation, CDK, Docker, Kafka
Responsibilities
Design and maintain CI/CD pipelines for ML models; Operationalize models for training and inference; Build and manage data pipelines and feature stores; Implement observability and monitoring for ML systems; Automate environment provisioning; Partner with security teams for compliance; Collaborate on productionizing prototypes.
Seniority
Mid-Senior, hands-on IC