Machine Learning Engineer
Posted on Nov 22, 2018 by MLB Advanced Media
Position: Machine Learning Engineer
Reports to: Director, Software Engineering, Baseball Data
Launched in 2001 as the tech arm of Major League Baseball, MLBAM is renowned for creating experiences that baseball fans love - and we're just getting started!
We're looking for an expert in Machine Learning to create the code powering baseball experiences?. The Baseball Data team is tasked with analyzing data captured on major league fields. With the launch of Statcast in 2015, MLB began capturing ball and player movements for each and every play. This role will involve combining our various data sources with video in near real-time to further our understanding of what is happening on the field. Potential projects involve analyzing limb movements of players, tracking the ball and player as they move across the diamond, detecting fielder shifts, scene detection and combing tracking data with LIDAR scans to validate the system.
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, our software is consumed by fans, broadcasters, stadiums, MLB Clubs and the league itself. We 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!
* Develop models for detecting elements in video, image, audio and data
* Brainstorm, discuss, and drive new advanced technology solutions for MLBAM products
* Build scalable deep 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
* Masters or PhD in Computer Science with a focus in machine learning
* Strong machine learning or computer vision background
* Programming Languages - Python, Java, R
* Deep Learning Tools - Tensorflow, Theano, Caffe, etc.
Goldman Sachs USA