Principal Machine Learning Engineer (Personalization, Matchmaking, & Player Experience AI) - Publishing Platform
Core
Define and drive modeling architecture for personalization, matchmaking, and social experiences across Riot's player ecosystem, transforming social graph and behavioral data into adaptive AI systems.
Role type
Principal Machine Learning Engineer (Personalization, Matchmaking, & Player Experience AI)
Builds
Adaptive, fair, and player-centric AI systems for matchmaking, community discovery, and personalized content.
Domain
Gaming / Player Experience AI / Social Graphs
Deliverable
production ML models
Required skills
Graph ML, Reinforcement Learning, Representation Learning, Real-time ML systems, Multi-objective optimization, Model observability, A/B testing design, Fairness auditing
Preferred skills
Trust & safety modeling, Live-service game backend integration, Vertex AI/SageMaker experience
Technologies
PyTorch, TensorFlow, JAX, Ray, Kafka, Flink, Redis
Responsibilities
Define modeling architecture for personalization and matchmaking; Architect multi-model systems combining skill, preference, trust, and safety signals; Develop models for skill inference and player behavior prediction; Build and optimize real-time inference systems; Drive adoption of advanced modeling approaches (contextual bandits, RL, graph ML); Partner on data schemas and feature pipelines; Define Responsible AI standards and implement fairness audits; Lead post-launch evaluations of algorithmic impact; Set organization-wide standards for model optimization and drift detection; Mentor senior ML engineers and data scientists.
Seniority
Principal, technical leadership & strategy
