Electronic Arts (EA) is looking to improve the velocity and quality of next-generation interactive experiences by discovering and evaluating AI methods for game testing.
Requirements
- 3+ years of experience spanning across the entire ML lifecycle (frame, gather/curate data, model, evaluate, deploy, observe)
- Fluent in Python and major ML frameworks (e.g., PyTorch) and skill with software development practices.
- Experience training models at scale (multi-GPU or distributed), strong understanding of ML fundamentals, MLOps, and best practices (e.g., reproducibility).
- Experience with: Reinforcement/Imitation Learning, Computer Vision (for video), Agents/LLMs, Uncertainty Quantification, Out-of-distribution detection.
- Experience with Distributed ML (e.g., DeepSeed).
Responsibilities
- Prototype, train, and ship AI tools that improve game testing efficiency, such as autonomous play-testing agents, test-case generation, anomaly/bug detection, and bug triaging.
- Translate ATOM's technology roadmap into experiments and deliverables, with support from lead and senior ML scientists
- Build reliable data pipelines from gameplay logs, video/frames, and telemetry; ensure data quality, labelling strategies, and reproducibility.
- Stay up-to-date on advancements in deep learning and GenAI through self-study, internal workshops, and external conferences.
Other
- This job is onsite of hybrid remote/in-office (3 days/week).
- BSc degree in Computer Science, Engineering or Mathematics, or equivalent experience.
- Graduate degree in Computer Science, Engineering, Mathematics, or related discipline.
- We value adaptability, resilience, creativity, and curiosity.
- We nurture environments where our teams can always bring their best to what they do.
