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 Generative AI team is researching and developing Machine Learning based game features that will enrich the experience of our players and transform the ways they interact with the FC game. 

In this role you will join our cross-functional team to research, develop and integrate Machine Learning models from ideation and requirement analysis to productizing their application in FC game features.

Your responsibilities:

• Research and evaluate Machine Learning models and techniques for application in fields that include but are not limited to: automatic speech recognition, natural language processing and procedural content generation.

• Tailor the functionality of these models and inference frameworks to fit FC’s requirements and target platform constraints. Integrate them into the game’s systems.

• Develop, optimize and polish game features that leverage these models to deliver them to FC players.

• Share knowledge on your work by directly engaging with other members of the game team to develop and ship features.

• Evangelize the craft through presentations and interactive demonstrations, promoting Machine Learning best practices and applications within the team.

• Stay abreast of the latest advancements in the Machine Learning field, consult with internal subject matter experts and collaborate with external AI technology vendors, in order to identify and prototype ML application opportunities within FC.

Required qualifications:

• BS in Computer Science, Mathematics or related field, or equivalent professional experience.

• Proficiency with C++ and Python.

• Professional experience with AI and Machine Learning along with their respective tools and frameworks.

• Proven record of building, deploying and maintaining Machine Learning applications in productized software.

• Experience with large language models (LLM) applications and retrieval-augmented generation (RAG) techniques.

Preferred qualifications:

• PhD or Masters degree in Computer Science, Mathematics or related fields.

• Experience with ML frameworks like PyTorch or TensorFlow.

• Experience in optimizing ML models for memory and compute constrained real-time environments.

• Experience in working with large volumes (GBs/TBs) of data.

• Experience in working with cloud technology and platforms. e.g. containers, Kubernetes, Azure or AWS.