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MLOps Engineer
Xcel Hires Management Solutions
posted 4mon ago
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Job Description
You will be in the Payroll of Xcelhires working with end customer. Mode of Work: Work from Office / Remote 2 Level of Technical Discussion with Team + 1 Client Interview. Built and executed at least 2 MLOps projects in AWS cloud using Sage maker 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 (sage maker, ECR, S3, lambda, step functions) is a must. Should able write Cloud Formation scripts for dev./test/prod environments. Knowledge in Python. Should be able to build Dockers images independently. AWS Code Commit 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 (cloud formation). For the purposes of this engagement, extensions will be minimal and limited to those required to support the four identified work streams. Maintain and create documentation on infrastructure usage and design (confluence, Github wikis, and 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-plat formed within the infrastructure.
Job Description:
Minimum of 6 years DevOps experience in AWS Cloud including managing ML Pipelines. Employment Type: Full Time, Permanent
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