AI Engineer Intern (Masters)

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 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 employs a state-of-the-art, cloud-based tech stack equipped with top-tier tools to support 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 create a scalable AI Platform.

You will report to the Senior Manager of the AI Platform team.

Responsibilities:

• Develop key AI infrastructure components to support end-to-end machine learning lifecycle operations.

• Establish scalable, secure, and reliable cloud-based platforms for large-scale data analysis, model development, validation, and deployment in real-time applications.

• Design and implement efficient, automated customer-facing processes and workflows that leverage AI platform technologies.

• Work with producers, data scientists, ML engineers, and game developers to seamlessly integrate machine learning solutions into live services, ensuring effective model deployment and performance in production environments.

• Design and implement cloud solutions using AWS, GCP, or Azure to support scalable machine learning workloads with high availability.

• Manage and operate commercial tools and platforms such as Databricks, AWS and GCP.

• Optimize the platform and deployed models for performance, security, scalability, and cost efficiency in real-time, live environments.

Qualifications:

• Currently enrolled in a Master's degree in Computer Science, Electrical Engineering or related fields focusing 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.

• Experience with Gen AI technologies like diffusion models and LLM.

You must be available for a full-time paid internship in the summer of 2026.

At this time, we are considering Masters students who will be enrolled in an accredited degree program in the summer of 2027, slated to graduate no earlier than December 2027. Applicants must be legally authorized to work in Canada on a full-time basis during the 16-week internship. Visa sponsorship is not available for this position.

Please ensure that your graduation date is visible on your resume.