Principal Machine Learning Engineer (Personalization, Matchmaking, & Player Experience AI) - Publishing Platform

About this role

Riot Data Scientists combine their wide technical expertise across data processing, automation, machine learning ("ML"), artificial intelligence ("AI"), and experimental design to inform decisions and develop data-powered products. As a Principal Machine Learning Engineer on the Publishing Platform Data team, you will define and drive the modeling architecture that powers personalization, matchmaking, and social experiences across Riot’s player ecosystem. You’ll partner closely with Product, Data Engineering, and Software Engineering to transform large-scale social graph, matchmaking, and behavioral data into adaptive, fair, and player-centric AI systems

Your work shapes how players connect, discover communities, and experience matchmaking that feels meaningful and equitable. Responsibilities: Define and lead the modeling architecture for personalization, matchmaking, social graph recommendations, and player/community discovery. ‘Architect multi-model systems combining skill, preference, trust, and safety signals for fair and meaningful matchmaking Develop models for skill inference, player behavior prediction, trust & safety signals, and multi-objective optimization across fairness, latency, and experience quality

Build and optimize real-time inference systems for personalized content, store offers, matchmaking, and player interactions at global scale. Drive adoption of advanced modeling approaches including contextual bandits, reinforcement learning, graph ML, and session-aware personalization. Partner with Data Engineering and Product to shape data schemas, feature pipelines, telemetry standards, and model observability across the ML lifecycle

Define Responsible AI standards and implement fairness audits, bias mitigation, transparency, and safety mechanisms for matchmaking and social systems. Lead post-launch evaluations of algorithmic impact on player sentiment, community health, and ecosystem stability. Set organization-wide standards for model optimization

Apply for this role on Riot Games’s official careers site.