Central Technology is the force multiplier, accelerating creative opportunity and progress at EA. We’re a world-class community of technologists, innovators, strategists, and orchestrators transforming interactive entertainment. Together, we power the platforms, AI-driven tools, live services, and infrastructure that ensure global scale, secure player experiences, and unlock bold new possibilities.
Infrastructure & Platform Services builds and runs the technology foundation for EA’s games. Our teams deliver the live services and backend infrastructure that are used to ship, scale, and operate secure, reliable game experiences for millions of players worldwide.
The Challenge Ahead
The AI Platform team delivers centralized AI resources across all Electronic Arts franchises, crafting AI and Generative AI solutions alongside a shared AI infrastructure for company-wide application. Our team supports initiatives such as data modeling, model training and fine-tuning, and agent development. We provide solutions and platforms that empower the future of game development, marketing, sales, and player experiences.
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 Senior Manager of the AI Platform team.
Responsibilities:
You will develop core AI platform components to support machine learning lifecycle workflows.
You will implement and maintain cloud-based infrastructure to support scalable ML workloads.
You will automate end-to-end AI workflows, building CI/CD pipelines for model deployment, containerised micro-services and metric instrumentation for model performance and monitoring.
You will work with data scientists, ML engineers and game developers to integrate ML models into production systems, support deployment, conduct testing and troubleshoot performance or reliability issues in live environments.
You will develop scripts, services or platform modules for feature pipelines, model orchestration, data-lake or lakehouse interactions.
You will monitor and optimise model performance, scalability, and cost-efficiency in production.
Qualifications:
3+ years of professional software engineering experience with a focus on AI/ML systems or platform development
Proficiency in Python programming
Familiarity with deep-learning frameworks (e.g., PyTorch) and an understanding of machine learning lifecycle --including model development, evaluation, deployment
Experience working with containerisation (Docker), orchestration (Kubernetes) and CI/CD pipelines in a cloud environment
Exposure to cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code tooling (e.g., Terraform, CloudFormation)
Experience with data-lake or lakehouse technologies (e.g., Spark, Redshift, Snowflake, or Trino)
Understanding of deploying and monitoring ML models in production, including performance, scalability, reliability and cost considerations.
Bonus:
Exposure to generative AI technologies (e.g., diffusion models, large language models)
Experience in a live service or gaming environment
Prior project work in end-to-end ML systems\
This is a hybrid remote/in-office role.