Description

You will manage and automate machine learning workflows and cloud infrastructure.

Responsibilities

• Build and maintain automated ML pipelines using SageMaker.
• Manage cloud infrastructure using Code as Infrastructure.
• Deploy and orchestrate AWS services including ECR, S3, Lambda, and Step Functions.
• Implement MLOps best practices across the development lifecycle.
• Maintain version control and CI/CD workflows using GitHub, GitHub Actions, and AWS CodeCommit.

Required Skills

• 5+ years of professional experience in MLOps or related roles.
• Proficiency with Python and Docker.
• Hands-on experience with AWS Cloud and SageMaker.
• Experience with AWS services: ECR, S3, Lambda, and Step Functions.
• Strong understanding of ML Pipelines and Data Science principles.
• Experience with CloudFormation and Infrastructure as Code.
• Proficiency with GitHub, GitHub Actions, and AWS CodeCommit.
• Any Graduate degree.

Key Skills

Education

Any Graduate