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Description & Requirements
As a leader in the gaming industry, EA SPORTS is leading transformational changes in game development and player experiences. We foster a collaborative environment where every team member helps shape the future of entertainment through innovation.
The FC QVE team is focusing on revolutionising game testing by building Gen AI systems and using advanced Machine Learning techniques. We have a versatile team that is responsible for the entire lifecycle of AI/ML models, from initial conceptualization and analysis to their full-scale integration. You will join this team and report to the QVE Technical Director.
Main Responsibilities:
Generative AI & ML Testing: Develop adversarial testing frameworks to detect biases, edge cases, and security flaws in ML and Generative AI models.
Speech & Gameplay Model Validation: Build testing systems for AI speech models and gameplay ML models, focusing on human-like quality, anomaly detection, and behavioural consistency.
Infrastructure & Pipelines: Architect internal APIs, CI/CD pipelines, and orchestration workflows to ensure high-capacity experimentation and observability.
Collaborative Improvement: Work across departments to guide models from early-stage research through to productized testing solutions for FC game features.
Operational Excellence: Boost engineering output by adopting advanced AI-assisted workflows and maintaining rigorous standards for code quality.
Core Requirements:
You have a Bachelor's degree in Computer Science, Mathematics, or a related technical field, or equivalent experience.
You have at least 5 years in game or tool engineering using C++ and C#.
You have at least 2 years of practical experience with Machine Learning and Generative AI.
Your programming skills are in Python and C++, with intrinsic knowledge of system design and distributed backends.
You have experience with console platforms, game development lifecycles, and testing ML-integrated game features.
Other Qualifications:
Advanced degree (Master's) in a relevant technical discipline.
Familiarity with frameworks such as TensorFlow or PyTorch.
Demonstrated history of deploying and maintaining ML models within commercial software environments.
Have knowledge and be passionate about the sport of football (soccer).