Job Posting: MLB Machine Learning Engineer

Position: Machine Learning Engineer, Baseball Data

Location: New York, NY

Reports to: Director, Software Engineering, Baseball Data

Description:
Major League Baseball’s Technology team is renowned for creating experiences that baseball fans love.

They’re looking for an expert in Machine Learning to create the code powering Major League Baseball. The Baseball Data team is tasked with analyzing the data captured on the field. With the launch of Statcast in 2015, MLB began tracking ball and player movements for each and every play. This role will involve combining their various data sources with video in near real-time to further their understanding of what is happening on the field.

This position offers the opportunity to collaborate with other world-class engineers, data scientists, product developers, and designers; contribute to award-winning and complex apps and systems; influence the innovation of products used by millions globally; and work in a highly collaborative, results-oriented, team environment.

Using bleeding edge technology, their software is consumed by fans, broadcasters, stadiums, MLB Clubs and the league itself. They are looking for Engineers that are passionate about building new technologies for the baseball industry, and this role will help usher in the next generation of experiences for fans of all ages!

Core Responsibilities:

  • Brainstorm, discuss, and drive new advanced technology solutions for MLB products
  • Build scalable machine learning algorithms
  • Influence the innovation of products used by millions of users worldwide
  • Present and explain complex models to non-technical stakeholders
  • Introduce technologies you feel passionate about

Qualifications:

  • Masters or PhD in Computer Science with a focus in machine learning
  • 3+ years experience working with machine learning
  • Deep knowledge of machine learning and statistical predictive modeling
  • Experience with numpy, pandas, and scikit Python libraries
  • Real-world application experience implementing CNNs, or RNNs/LSTMs
  • Deep Learning Tools – Tensorflow, Theano, Caffe, etc.

To Apply:
To apply, please visit this site and complete the application.

The content in this posting was created and provided solely by Major League Baseball.





Meg is the managing editor of FanGraphs and the co-host of Effectively Wild. Prior to joining FanGraphs, her work appeared at Baseball Prospectus, Lookout Landing, and Just A Bit Outside. You can follow her on twitter @megrowler.

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Mac
4 years ago

Has anyone from the Fangraphs community been hired after seeing a job post on here? Would love to hear a success story.

Josermember
4 years ago
Reply to  Mac

I think they’re all on the Top Gun downlow. You know, they could tell you but then…