Staff Applied AI/ML Scientist - Central Technology, Anti-Cheat
Core
Lead modeling strategy and build production-ready AI/ML systems to detect cheaters and botters across Riot's competitive game titles and platforms.
Role type
Staff Applied AI/ML Scientist (Anti-Cheat)
Builds
Production ML classifiers, anomaly detection systems, and ML infrastructure for competitive integrity products.
Domain
Gaming / Anti-Cheat / Machine Learning
Deliverable
production ML models
Required skills
Ph.D. in ML/AI/Stats/Math or equivalent, 3+ years industry experience, 2+ years anti-cheat/fraud/security experience, production ML systems expertise, model serving, CI/CD for ML, observability, deep learning, traditional ML models, complex/unconventional data sources, feature engineering, technical discovery, prototyping, mentoring.
Preferred skills
Iterative machine classifiers for behavioral anomalies in video games, threat detection in gaming/risk/fraud/security/sports, bridging research and production, passion for games/player experience.
Technologies
Deep learning frameworks, traditional ML libraries, CI/CD pipelines, observability tools, centralized ML infrastructure.
Responsibilities
Design and maintain end-to-end AI/ML pipelines for iterative classifiers; innovate in anomaly detection with novel modeling approaches; leverage and upgrade centralized ML infrastructure; analyze and develop prototypes for emerging anti-cheat challenges; refine modeling strategy and feature invention; develop mission-critical ML systems from scratch; lead technical discovery and prototyping; mentor junior staff.
Seniority
Staff, hands-on IC with strategic impact and mentorship.
