Description
Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.
The Infrastructure and Platform Services (IPS) team serves as the backbone of EA's global ecosystem, supporting the creation of exceptional games and immersive player experiences. We offer essential platforms such as Cloud, Commerce, AI, Gameplay Services, Identity, and Social. By delivering reusable capabilities, we enable game teams to seamlessly integrate our services, allowing them to concentrate on crafting some of the world's best games and fostering meaningful connections with players.
As the driving force behind the scenes, we ensure everything works in harmony. Join us in shaping the future of play.
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:
- Develop core AI platform components to support machine learning lifecycle workflows.
- Implement and maintain cloud-based infrastructure to support scalable ML workloads.
- Automate end-to-end AI workflows, building CI/CD pipelines for model deployment, containerised micro-services and metric instrumentation for model performance and monitoring.
- 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.
- Develop scripts, services or platform modules for feature pipelines, model orchestration, data-lake or lakehouse interactions.
- 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