The EA Digital Platform (EADP) group is the core powering the global EA ecosystem. We provide the foundation for all of EA's incredible games and player experiences with high-level platforms like Cloud, Commerce, Data and AI, Gameplay Services, Identity and Social. By providing reusable capabilities that game teams can easily integrate into their work, we let them focus on making some of the best games in the world and creating meaningful relationships with our players. We're behind the curtain, making it all work together. Come power the future of play with us.
The Challenge Ahead
The Data & AI Group provides unified AI resources across all franchises within Electronic Arts. Our group develops AI and data-driven solutions, as well as common AI infrastructure for use in every facet of the company. From data-modeling to agent-building, we use a modern, cloud-based tech stack with the best tools to provide solutions and platforms empowering the future of game development, marketing, sales, and player experience.
As a Software Engineer with expertise in AI/ML systems and platform development, you will help lead the creation of a scalable AI Platform .
You will report to the Technical Director of the Data & AI team.
Responsibilities:
- You will architect and develop core AI infrastructure components, the foundation for end-to-end ML lifecycle operations.
- You will establish scalable, secure and available cloud-based platforms, for large-scale data analyses, model development, model validation and model deployment for real-time applications.
- You will design and implement efficient and automated customer-facing processes and workflows supporting AI platform technologies.
- You will work with AI Scientists to deploy ML models as part of production systems. Examples include predictive learning applications, like bad-actor detection, or content-generative applications like in-game assets creation.
- You will collaborate with producers, ML engineers, and game developers on ML solutions, built on top of platform technologies to ensure scalable and performance-optional.
- You will manage and operate commercial tools and platforms, such as Databricks, AWS Sagemaker.
Qualifications:
- 3+ years of software engineering experience with a focus on AI/ML systems or platform development.
- Proficiency in Deep Learning frameworks like PyTorch.
- Proficiency in Python programming.
- Experience in CI/CD, containerization and orchestration tools such as Docker and Kubernetes.
- Experience designing and building scalable cloud-based solutions for machine learning lifecycle.
- Experience with cloud platforms (AWS, GCP, or Azure) and cloud-native tools (e.g. terraform) for managing infrastructure.
- Experience deploying and managing machine learning models in production for real-time applications.
- Experience with one or more data lakehouse solutions, like Snowflake, Trino, Redshift, or Spark.