MLOps Engineer

3 weeks ago


Hyderabad, India Blend Full time

Responsibilities


  • Maintain and extend existing data science pipelines in AWS, with an emphasis on infrastructure as code (cloudformation)
  • For the purposes of this engagement, extensions will be minimal and limited to those required to support the four identified workstreams.
  • Maintain and create documentation on infrastructure usage and design (confluence, github wikis, diagrams)
  • Serve as the internal infrastructure expert, providing guidance to data scientists deploying models into the pipelines
  • Research new optimization opportunities based on the needs of specific data science products
  • Work independently and collaboratively with data scientists to implement optimizations and improvements to specific projects deploying or being re-platformed within the infrastructure.


Qualifications


  • Minimum of 5 years DevOps experience in AWS Cloud including managing ML Pipelines.
  • Built and Executed at least 2 MLOps projects in AWS cloud using Sagemaker or other services.
  • Experience building cloud infrastructure as code
  • Expertise in MLOps best practices
  • Foundational understanding of Data Science and Data Acience best practice
  • Experience AWS services (sagemaker, ECR, S3, lambda, step functions) is a must
  • Should be able to write CloudFormation scripts for dev/test/prod environments
  • Knowledge in Python
  • Should be able to build Docker images independently
  • AWS CodeCommit or Github (including Github actions) experience is a must


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