Principal Data Scientist (AI, Gaming)

TL;DR

Principal Data Scientist (AI, Gaming): Defines and drives the modeling architecture for personalization, matchmaking, and social experiences across Riot’s player ecosystem with an accent on transforming large-scale social graph, matchmaking, and behavioral data into adaptive AI systems. Focus on architecting multi-model systems, developing skill inference and prediction models, and optimizing real-time inference at global scale.

Location: Must be based in the United States, with operations subject to California, Los Angeles, San Francisco, and Washington state fair chance acts. The company offers flexible work schedules.

Company

Riot Games is a product company dedicated to creating games and experiences that prioritize the delight of players.

What you will do

• Define and lead the modeling architecture for personalization, matchmaking, and player/community discovery systems.
• 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, and multi-objective optimization across key metrics.
• Build and optimize real-time inference systems for personalized content, store offers, and player interactions at global scale.
• Drive adoption of advanced modeling approaches including contextual bandits, reinforcement learning, and graph ML.
• Define and implement Responsible AI standards, fairness audits, and bias mitigation mechanisms for matchmaking and social systems.

Requirements

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

Nice to have

• Professional background in gaming, player modeling, or social ecosystems.
• Experience with trust & safety, toxicity detection, or community health models.
• Familiarity with Vertex AI, SageMaker, or internal large-scale inference systems.
• Experience integrating ML systems with live-service game backends.

Culture & Benefits

• Open paid time off policy and flexible work schedules promoting work/life balance.
• Comprehensive medical, dental, and life insurance.
• Parental leave for employees, spouses/domestic partners, and children.
• 401k with company match.
• Emphasis on player empathy and a collaborative team environment.