Tech Stack

Description

You will define and drive the modeling architecture for personalization, matchmaking, and social experiences across Riot's player ecosystem, partnering with Product, Data Engineering, and Software Engineering to transform large-scale data into adaptive, fair, and player-centric AI systems that shape how players connect and experience matchmaking.

Requirements

• 10+ years in ML/Applied AI; 3+ years in principal/staff-level technical leadership
• Experience with large-scale, real-time ML systems (recommendations, personalization, matchmaking)
• Expertise in graph ML, RL, and representation learning
• Proficiency in PyTorch, TensorFlow, JAX, and modern data/serving tools (Ray, Kafka, Flink, Redis)
• Strong grounding in A/B testing, experiment design, and experience metrics

Responsibilities

• Define and lead modeling architecture for personalization, matchmaking, social graph recommendations, and player discovery
• Architect multi-model systems combining skill, preference, trust, and safety signals for fair matchmaking
• Develop models for skill inference, player behavior prediction, and multi-objective optimization
• Build and optimize real-time inference systems for personalized content, matchmaking, and player interactions at global scale
• Drive adoption of advanced modeling including contextual bandits, reinforcement learning, graph ML, and session-aware personalization