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Electronic Arts

AI Engineer Intern

Vancouver, BC, Canada

Posting language: English
Posted: Oct 1, 2026

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Original job description

General Information

Locations: Vancouver, British Columbia, Canada

Role ID

216223

Worker Type

Intern - Temporary Employee

Studio/Department

CT - Infrastructure & Platform

Work Model

Hybrid

Description & Requirements

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 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 Bachelor'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 Bachelor's 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.

Pay Transparency - North America

British Columbia (depending on location e.g. Vancouver vs. Victoria) *$65,000 - $70,000 CAD

Pay is just one part of the overall compensation at EA.

About Electronic Arts

We’re proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth.

We adopt a holistic approach to our benefits programs, emphasizing physical, emotional, financial, career, and community wellness to support a balanced life. Our packages are tailored to meet local needs and may include healthcare coverage, mental well-being support, retirement savings, paid time off, family leaves, complimentary games, and more. We nurture environments where our teams can always bring their best to what they do.

Electronic Arts is an equal opportunity employer. All employment decisions are made without regard to race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, genetic information, religion, disability, medical condition, pregnancy, marital status, family status, veteran status, or any other characteristic protected by law. We will also consider employment qualified applicants with criminal records in accordance with applicable law. EA also makes workplace accommodations for qualified individuals with disabilities as required by applicable law.

Apply About employer

More about this job

Responsibilities

Develop and maintain scalable AI infrastructure components to support the end-to-end machine learning lifecycle. Collaborate with cross-functional teams to integrate machine learning solutions into live services and optimize platform performance.

Requirements

Candidates must be currently enrolled in a Bachelor's degree program in Computer Science, Electrical Engineering, or a related field. Proficiency in Python, Deep Learning frameworks, and experience with cloud platforms and containerization tools is required.

Skills

Python
PyTorch
Deep learning
Machine learning
Cloud computing
AWS
GCP
Azure
Docker
Kubernetes
CI/CD
Terraform
Generative AI
LLM
Data modeling

Benefits

Healthcare coverage
Mental well-being support
Retirement savings
Paid time off
Family leaves
Complimentary games

Visa sponsorship

Not detected in the job text

Keywords

AI Engineer
Machine Learning
Infrastructure
Cloud-based
Generative AI
Python
PyTorch
Docker
Kubernetes
AWS
GCP
Azure
Terraform
Databricks
Snowflake
Trino
Redshift
Spark
LLM
Diffusion models
CI/CD
Data lakehouse
Software engineering
Model training
Real-time applications

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