Role overview
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 ATOM team builds the future of AI for testing games. As a Machine Learning Engineer reporting to the Director of AI, you will fulfill high-impact applied research goals and help us bring EA's games to life. Your mission is to discover and evaluate AI methods that increase the velocity and quality of next-generation interactive experiences. Our team impacts every title in EA's portfolio, and you will work with all types of AI technology to improve our titles.
What you'll work on
- 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.
- This job is onsite of hybrid remote/in-office (3 days/week).
What we're looking for
- BSc degree in Computer Science, Engineering or Mathematics, or equivalent experience.
- 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).
Preferences
- Graduate degree in Computer Science, Engineering, Mathematics, or related discipline.
- Experience with: Reinforcement/Imitation Learning, Computer Vision (for video), Agents/LLMs, Uncertainty Quantification, Out-of-distribution detection.
- Experience with Distributed ML (e.g., DeepSeed).
Compensation And Benefits
The ranges listed below are what EA in good faith expects to pay applicants for this role in these locations at the time of this posting. If you reside in a different location, a recruiter will advise on the applicable range and benefits. Pay offered will be determined based on a number of relevant business and candidate factors (e.g. education, qualifications, certifications, experience, skills, geographic location, or business needs).