Machine Learning Engineer

Technology & Design Team
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Job Description

• Optimize workflows when developing and deploying machine learning models.
• Explore and optimize our existing technology stack, finding ways to reduce query times, speed up model development, maximize utilization of resources, and maximize cluster uptime - this may come through experimenting with different open source technology stacks in sandbox / dev environments, evaluating potential tools from external vendors, and empowering the other advance analytics team members are implementing best practices in MLOps.
• Ensure that the machine learning models deployed in production are functioning as expected.
• Explore other ways to improve Mynt Advance Analytics workflows by building internal tools, machine learning libraries and microservices (such as our internal REST APIs, Job scheduling API, etc.)
• Monitor and maintain uptime of the DS team's technology stack, which includes Kubernetes, Apache Spark, Apache Zeppelin, Jupyterhub, RStudio, R Shiny and internal REST APIs.

  • Bachelor’s degree graduate
  • At least 2 years experience deploying and maintaining machine learning models in production
  • Must possess strong knowledge and skills in Spark, Hadoop, Kubernetes, Docker and other related tools
  • Proficient in data science toolsets such as JupyterHub, RStudio and others.
  • Strong knowledge and deep understanding of  Data Science and Analytics
  • Strong knowledge and deep understanding of MLOps or DevOps practices.

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