Senior MLOps Engineer (AWS & GenAI)

Quick Facts

• Role: Senior MLOps Engineer (AWS & GenAI)

Description

Design and maintain cloud-native ML platforms on AWS and build end-to-end MLOps pipelines for GenAI and ML models in production. You will containerize services and automate deployments using CI/CD, while ensuring operational health and reliability. Apply cloud security and networking best practices (VPC/IAM) across distributed engineering teams.

Responsibilities

• Design and maintain cloud-native ML platforms using AWS services such as SageMaker, Bedrock, ECS/EKS, and Lambda, with Infrastructure as Code (AWS CDK, Terraform, CloudFormation)
• Build, automate, and support end-to-end MLOps pipelines using SageMaker Pipelines, MLflow, and CI/CD tooling
• Containerize applications (Docker/Kubernetes), ensure seamless deployments, and manage operational health for GenAI/ML models in production
• Apply cloud security and networking (VPC/IAM) and operational best practices across engineering, platform, and product teams

Requirements

• Hands-on experience operating ML platforms and supporting GenAI workloads using AWS SageMaker and AWS Bedrock (or similar)
• Strong cloud engineering expertise with AWS services (e.g., S3, Lambda, EC2, IAM, VPC) and Infrastructure as Code (AWS CDK, Terraform, or CloudFormation)
• Proficiency in containerizing applications with Docker and Kubernetes (EKS/ECS) and building CI/CD pipelines with GitHub Actions or Jenkins
• Solid coding skills in Python and an understanding of the end-to-end Machine Learning lifecycle
• Deep understanding of cloud security, networking, and cross-functional collaboration

Benefits

• Opportunity to work hands-on on AWS GenAI/ML platforms and production MLOps pipelines across multiple engineering teams