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EA SPORTS revolutionizes the world of gaming by creating transformational change in how games are made and played.. At EA SPORTS, everyone contributes to creating the future of entertainment, building a community where creativity and new ideas grow.
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 developers 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 realise 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 several ongoing and legacy ML projects inside our franchise. You will work with ML and traditional SEs, and animators to achieve technical growth and help sculpt a technology roadmap that meets our production needs. You will report to the Technical Director of Research and Innovation.
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 with the development team to support experiments with tooling and systems, and data acquisition and management
- Share your results through presentations, papers, prototypes and compelling interactive demonstrations
- Stay up to date with the latest advancements in relevant technologies and propose impactful projects to drive innovation
- Collaborate with a range of team members including production, design, and artists.
Your Qualifications:
- PhD or Masters with research experience in Computer Science, mathematics or related fields.
- 3+ years of 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 development, and experience going from idea to implementation
- Experience turning new ideas into implementations