Description

You will manage and automate machine learning lifecycles within AWS environments.

Responsibilities

• Build and maintain automated ML pipelines using SageMaker.
• Deploy and orchestrate services using AWS Lambda, Step Functions, and ECR.
• Manage cloud infrastructure using Infrastructure as Code principles.
• Implement MLOps best practices to streamline data science workflows.

Required Skills

• 5+ years of experience in MLOps or related engineering roles.
• Proficiency with AWS Cloud services including S3, ECR, Lambda, and Step Functions.
• Hands-on experience with SageMaker and ML pipeline orchestration.
• Strong Python programming skills.
• Experience with Docker containerization.
• Working knowledge of CloudFormation for infrastructure management.
• Proficiency with AWS CodeCommit and GitHub/GitHub Actions.
• Understanding of Data Science fundamentals.

Preferred Skills

• Any Graduate degree.

Key Skills

Education

Any Graduate