Electronic Arts

EA SPORTS is at the forefront of revolutionizing the world of gaming by driving transformational change in how games are made and played.. At EA SPORTS, everyone contributes to crafting the future of entertainment, building a community where creativity and innovation thrive.

The FC Gameplay Advanced Team makes meaningful innovations in team strategy, AI, player animation, and player interactions that create exciting back of the box features for the EA Sports FC franchise.  We work with creative designers, artists, and engineers to deliver big ideas that matter to the millions of players who enjoy the biggest sports video game in the world.

As a Machine Learning Scientist, you will realize the team’s research roadmap by combining the latest research inside and outside of EA and applying it to video games.  We are looking for an expert that oversees the system designs and ML techniques used across our various ongoing and legacy ML projects inside our franchise.  You will be working with ML and traditional SEs, and animators to drive technical growth and help sculpt a technology roadmap that meets our production needs.

• Your Responsibilities:

  • Contribute to the ML research strategy to create new player experiences, exploring frontier technologies to shape the future of the FC Franchise

  • Work closely with the engineering team to support experiments with tooling and systems, as well as data acquisition and management

  • Share your results through presentations, papers, prototypes and compelling interactive demonstrations

  • Stay abreast of the latest advancements in relevant technologies and propose impactful projects to drive innovation

  • Collaborate with a range of internal stakeholders including production, design, and artists.  

• Your Qualifications:

  • PhD or Masters with extensive research experience in Computer Science, mathematics or related fields.

  • Experience with machine learning and familiarity with multiple ML techniques such as transformer models and diffusion models

  • Python programming experience with ML frameworks like PyTorch or TensorFlow

  • Technical background, experience working with both research engineering, and a proven track record of going from idea to implementation

  • Demonstrated success in turning new ideas into effective implementations