Machine Learning Engineer

March 26

Zelus Analytics

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Building the world's best sports intelligence platform.

11 - 50

Description

• Develop, validate, and automate quantitative models using statistics, machine learning, optimization, and simulation • Develop, schedule, monitor, and maintain model training and prediction workflows • Coordinate with broader engineering team to plan and implement changes to core infrastructure to support one or more sports • Collaborate with data scientists to define and manage model productionalization and platform release plans • Deploy REST APIs on top of fitted models using distributed computation to support real-time, client-facing integration • Collaborate and communicate effectively in a distributed work environment • Fulfill other related duties and responsibilities, including rotating platform support

Requirements

• Academic and/or industry experience in back-end software design and development • Academic, industry, and/or research experience with applied mathematical and predictive modeling (statistics, machine learning, optimization, and/or simulation) • Experience with cloud infrastructure and distributed computing • Fluency with Python (preferred), R, Scala, and/or other data-oriented and statistical programming languages • Experience with relational databases and SQL development • Familiarity working with Linux servers in a virtualized/distributed environment • Strong software-engineering and problem-solving skills

Benefits

• Meaningful mentorship opportunities • Opportunity for skill development • Inclusive and diverse work environment • Support for building a successful career