MLOps Engineer--PD

Role : MLOps Engineer

Experience : 5 to 7 Years

Work Location : Hyderabad

Notice period: Immediate to 15 days

Job Description:

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.

Skills:

Experience building cloud infrastructure as code

Expertise in MLOps best practices

Foundational understanding of data science and data science best practice

Experience AWS services (sagemaker, ECR, S3, lambda, step functions) is a must

Should able 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

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.

Technical Skills: AWS Cloud, MLOps, SageMaker, CloudFormation, Python, Docker, AWS ECR, AWS S3, AWS Lambda, AWS Step Functions, AWS CodeCommit, GitHub, GitHub Actions