- 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 current topics, services and enhancements in Cloud Technologies
Preferred candidate profile
📌 Machine Learning Engineer (Pune)
🏢 Infosys
📍 Pune
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