ML Engineering Intern

Location: Tiburon/Vancouver/Stockholm/Remote
Duration: 12 weeks

Electronic Arts is looking for a passionate ML Engineering Intern to develop an AI authenticity model that enhances quality assurance for our sports titles. The model will evaluate gameplay against real-world sports rules, player behaviors, and authenticity standards, helping QA teams identify when game scenarios deviate from realistic outcomes. This role is an exciting opportunity to combine AI/ML research with practical game quality testing and help ensure EA’s sports games deliver the most authentic experiences possible.

Key Responsibilities

• Research and design an AI authenticity framework that can assess gameplay events, animations, and outcomes in EA sports titles. 
• Build machine learning models to compare in-game scenarios against real-world sports data and authenticity benchmarks. 
• Develop tooling that integrates the authenticity model into EA’s QA pipelines for automated test evaluation. 
• Collaborate with QA, gameplay engineers, and data scientists to define authenticity criteria and refine model accuracy. 
• Document methodologies, results, and guidelines for scaling the authenticity model across multiple sports titles.
   

Required Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related fields. 
• Strong programming skills in Python (ML/data stack: TensorFlow, PyTorch, scikit-learn, etc.). 
• Understanding of machine learning model development, training, and evaluation. 
• Knowledge of sports rules, mechanics, or gameplay systems. 
• Strong problem-solving and analytical skills, with an ability to translate abstract authenticity concepts into measurable signals.
   

Preferred Qualifications

• Prior experience with computer vision, NLP, or reinforcement learning for modeling real-world behaviors. 
• Familiarity with game data pipelines or telemetry analysis. 
• Coursework or projects related to sports analytics. 
• Experience with large-scale datasets and model deployment.
   
   

What You’ll Gain

• Hands-on experience applying AI/ML to real-world game QA challenges. 
• Direct impact on how EA ensures authenticity and realism in sports games. 
• Mentorship from engineers and researchers at the intersection of gaming and AI. 
• An opportunity to contribute to innovations that shape the future of sports gaming experiences.