Job description

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 (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 Required Qualifications: 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. Track record of setting ML strategy and standards across teams. Desired Qualifications: 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. 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! Our Perks: 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. Check out our benefits pages for more information. 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. It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act. Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories: Safeguarding confidential and sensitive Company data Communication with others, including Rioters and third parties such as vendors, and/or players, including minors Accessing Company assets, secure digital systems, and networks Ensuring a safe interactive environment for players and other Rioters These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security. (Los Angeles Only) Base salary range between $292,300.00 - $437,900.00 USD + incentive compensation + equity + 401K with company match + medical, dental, vision, and life insurance + short and long-term disability + open PTO.

Requirements

Must-haves

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
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.
Track record of setting ML strategy and standards across teams.
Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:
Safeguarding confidential and sensitive Company data
Communication with others, including Rioters and third parties such as vendors, and/or players, including minors

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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlai

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto

Paid Time Off

Parental Leave