Machine Learning Engineer

Company: SecureKloud Technologies Inc.
Location: San Francisco, California, United States
Type: Full-time
Posted: 10.JUN.2021

Summary

Job Responsibilities: * Research and implement MLOps tools, frameworks and platforms for our Data Science projects. * Work on a backlog...

Description

Job Responsibilities:


  • Research and implement MLOps tools, frameworks and platforms for our Data Science projects.

  • Work on a backlog of activities to raise MLOps maturity in the organization.

  • Proactively introduce a modern, agile and automated approach to Data Science.

  • Conduct internal training and presentations about MLOps tools' benefits and usage.

  • Management and development of continuous integration and deployment

  • Prototyping and developing cloud-native architecture solutions for application needs, particularly with AWS

  • Providing infrastructure-as-code utilizing Terraform and AWS Cloud Formation


Requirements:


  • Wide experience with Kubernetes and Docker is a must have

  • Experience in operationalization of Data Science projects (MLOps) using at least two one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, h2O etc).

  • Good understanding of ML and AI concepts. Hands-on experience in ML model development

  • Proficiency in Python used both for ML and automation tasks. Good knowledge of Bash and Unix command line toolkit.

  • Experience in CI/CD/CT pipelines implementation.

  • Experience with AWS cloud platforms is a must have.

  • Providing infrastructure-as-code utilizing Terraform and AWS Cloud Formation

  • Experience with Data Science IDE tools like Jupyter Notebook and RStudio

- provided by Dice

 
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