Electronic Arts is looking to develop an AI authenticity model to enhance quality assurance for their sports titles by evaluating gameplay against real-world sports rules, player behaviors, and authenticity standards.
Requirements
- 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.
- Prior experience with computer vision, NLP, or reinforcement learning for modeling real-world behaviors.
- Familiarity with game data pipelines or telemetry analysis.
- Experience with large-scale datasets and model deployment.
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.
Other
- Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related fields.
- 12 weeks duration
- 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.
- British Columbia (depending on location e.g. Vancouver vs. Victoria) *$83,000 - $116,400 CAD
