Machine Learning Engineer

Role - ML Ops - AWS Cloud

Location - Any Tech M location

Exp - 6 yrs and above

NP - Immediate - 30 days

Mandatory Skills

• Good working knowledge of AWS Cloud, including services like IAM, S3, KMS, Athena, API Gateway, Load Balancers, CloudWatch Logs, CloudTrail, VPC, Subnets and Security Groups.
• Good working knowledge of CI/CD and Infrastructure as Code techniques, including experience on tools like GitHub and especially leveraging Terraform for Infrastructure provisioning in AWS Cloud
• Strong expertise in AWS Cloud services, including but not limited to Lambda, API Gateway, Bedrock, DynamoDB, S3, SageMaker, IAM with a focus on GenAI workloads.
• Strong expertise in Python programming for building, deploying, and managing reusable GenAI components, including integration with AWS services and unit testing.
• Strong expertise with Terraform for infrastructure provisioning and management in AWS, ensuring scalable, secure, cost-efficient deployments.
• Solid understanding of CI/CD pipelines using GitHub Actions, including automating testing, deployment, and monitoring workflows for GenAI components.
• Knowledge of ML metadata tracking tools (e.g., MLflow, SageMaker Model Registry).
• Build CI/CD workflows for ML model lifecycle management using AWS services (e.g., SageMaker, Lambda, Step Functions, CodePipeline).