Description
Electronic Arts is seeking an AI Engineer Intern to join its Infrastructure and Platform Services team. The successful candidate will contribute to developing a scalable AI platform, reporting to the Senior Manager of the AI Platform team.
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. The team uses 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.
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.
- Collaborate with producers, data scientists, ML engineers, and game developers to seamlessly integrate machine learning solutions into live services.
- 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.
The internship is full-time and paid, lasting 16 weeks during the summer of 2026. Applicants must be legally authorized to work in Canada on a full-time basis during the internship. Visa sponsorship is not available for this position.