ML Ops Engineer
Posted Updated
Summary
ML Ops Engineer who builds and maintains automated DevOps/MLOps workflows in Python, runs CI/CD with Jenkins and Git, deploys containerized apps on Docker/Amazon EKS, provisions AWS services (SageMaker, Lambda, S3, ECS, IAM, RDS), and operates ML pipelines using CloudFormation/Terraform IaC and Databricks.
Role & responsibilities:
- Design, develop, and maintain automated DevOps and MLOps workflows using Python scripting and automation.
- Manage CI/CD pipelines using Jenkins and Git to support efficient software and machine learning model deployment.
- Build, deploy, and maintain containerised applications using Docker, with troubleshooting support for Amazon EKS environments.
- Provision, configure, and manage AWS services, including SageMaker, Lambda, S3, ECS, IAM, and RDS.
- Develop and maintain Infrastructure as Code (IaC) solutions using AWS CloudFormation (CFT) and Terraform.
- Build, deploy, and operate machine learning pipelines across platforms such as Amazon SageMaker, Databricks, and AWS Lambda.
- Troubleshoot infrastructure, deployment, and pipeline issues to ensure reliable and efficient operations.