ML Engineering Intern at Electronic Arts

ML Engineering InternLocation: Tiburon/Vancouver/Stockholm/Remote Duration: 12 weeksElectronic 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 ResponsibilitiesResearch 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 QualificationsCurrently 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 QualificationsPrior 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 GainHands-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. Apply Now