Machine Learning Engineer

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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.

Responsibilities

• 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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