Machine Learning Engineer

Job description

**Role & responsibilities** - 3+ yrs DevOps/Cloud/ML Ops experience; Python for scripting and automation - Strong with Jenkins, Git, Docker, EKS troubleshooting - AWS: SageMaker, Lambda, S3, ECS, IAM, RDS, infra creation - IaC: CloudFormation (CFT) and Terraform - ML Ops: build/operate ML pipelines deploying to SageMaker, Databricks, or Lambda - **MLOps Implementation and Support Experience** - **Python Programming is Mandatory** - **DevOps Working knowledge with implementation experience** - Understand and take requirements on Operationalization of ML Models from Data Scientist - Help team with ML Pipelines from creation to execution - List Azure services required for deployment, Azure Data bricks and Azure DevOps Setup - Assist team to coding standards (flake8 etc) - Guide team to debug on issues with pipeline failures - Engage with Business / Stakeholders with status update on progress of development and issue fix - Automation, Technology and Process Improvement for the deployed projects - Setup Standards related to Coding, Pipelines and Documentation - Adhere to KPI / SLA for Pipeline Run, Execution Research on new topics, services and enhancements in Cloud Technologies **Preferred candidate profile**