Senior MLOps Engineer

12 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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Senior MLOps Engineer

Key Responsibilities
  • Partner with Data Scientists to convert research models into scalable production workflows.
  • Build & operate ML pipelines on

    AWS SageMaker, Step Functions, ECS/Lambda, ECR, S3

    .
  • Implement batch processing, caching, and low-latency services with

    DynamoDB + DAX

    .
  • Manage CI/CD for ML (GitHub Actions, Terraform) across environments.
  • Enable monitoring, alerting, and cost optimization with

    CloudWatch

    .
  • Ensure security best practices (IAM, encryption, private networking).
Required Skills
  • 6+ years

    in MLOps/ML Engineering with production ML workflows.
  • Strong expertise in

    AWS ML stack (SageMaker, Step Functions, Lambda, ECS, DynamoDB, DAX)

    .
  • Proficiency in

    Python, Docker, CI/CD, Terraform/GitHub Actions

    .
  • Solid experience in

    model deployment, monitoring, and cost management

    .
  • Strong collaboration with Data Science & Engineering teams.
Why Join Us?
  • Opportunity to

    own end-to-end MLOps

    in a data-driven environment.
  • Work with cutting-edge

    AWS ML/AI solutions

    at scale.
  • Collaborative, growth-focused culture with real impact on analytics-driven decisions.


Apply now and be part of our journey to build reliable, secure, and scalable ML pipelines!


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