Staff Applied AI/ML Scientist (Central Technology, Anti-Cheat)

Join Riot Games as a Staff Applied AI/ML Scientist in the Anti-Cheat team. You will build machine learning-driven detection systems to identify cheating and abuse in multiplayer games. Collaborate with anti-cheat experts, game product teams, and engineering teams to ensure a safe and fair gaming environment. You will report to the Senior Manager of Anti-Cheat Data and Analytics.

• Design, train, and deploy real-time machine learning models to detect gameplay anomalies, automated bots, and memory-tampering exploits.
• Build scalable inference pipelines capable of evaluating millions of high-throughput game actions per second with minimal latency impact.
• Establish robust ML Ops practices, including automated model retrain loops and continuous monitoring for adversarial drift.

• Excellent written and verbal communication with both technical and nontechnical stakeholders
• Deep understanding of traditional machine learning models, and production deployment experience in at least one domain: computer vision, graph neural networks, transformer architectures, or agentic systems
• Bachelor’s degree or higher in Computer Science, Machine Learning, Statistics, or a related quantitative field, or equivalent practical experience
• For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role!
• 6+ years of experience delivering ML systems in production, including 3+ years in applied modeling or ML research roles
• Product owner's mindset, to be able to identify opportunities for impact and then see them through to production
• Demonstrated history of quickly delivering impactful machine learning solutions for critical business problems
• Track record mentoring engineers across roles and levels; evidence of raising the bar for people around you
• Working understanding of Windows internal mechanics (e.g. processor memory, driver architecture, etc.) and how adversarial software can leverage them to bypass security controls
• Understanding of high-performance competitive multiplayer games and the challenges associated with them
• Experience defining telemetry or instrumentation needs in close partnership with software or data engineers
• Familiarity with relational databases (e.g., MySQL, Postgres), document stores (e.g., ElasticSearch), and distributed storage systems (e.g., HDFS, S3, Google Cloud Storage)
• Experience working in adversarial detection (e.g. information/cyber security, fraud, money laundering, cheating, etc)