Principal Data Scientist (Personalization, Matchmaking, & Player Experience AI) - Publishing Platform

Riot Games • Los Angeles, CA

6h

About The Position

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 Data Scientist 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.
For this role, you'll find success through craft expertise and a collaborative spirit that prioritizes the delight of players. We will look at your past studies and experience, but for this role, we also look for dedicated people with a personal relationship with games. If you embody player empathy and care about players' experiences, this is the role for you!
At Riot Games, we put players first. That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.

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 (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.
• Track record of setting ML strategy and standards across teams.

Nice To Haves

• 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.

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 (latency, throughput, memory), multi-model orchestration, and drift detection.
• Mentor senior ML engineers and data scientists, influencing system design, experimentation strategy, and modeling craft across organizations.
• Represent the ML discipline in cross-functional design reviews, driving alignment on technical decisions, data contracts, and long-term strategy

Benefits

• Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules.
• We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed