Job description

ML engineers at Riot own the full lifecycle of machine learning in production — from problem framing through model design, deployment, and operation — building systems that serve players at global scale. They work across disciplines with engineers, data scientists, designers, and product teams to turn ML capabilities into player-facing experiences and tools for making great games. The Role As a Principal AI/ML Platform Engineer for League of Legends , you’ll be a well-rounded machine learning engineer with deep expertise in ML platforms, setting the technical direction for the systems that enable teams to build, launch, and operate ML-powered experiences at global scale. The role requires strong, hands-on ML engineering depth and a practical understanding of how models are developed, trained, evaluated, deployed, served, monitored, and iterated in production. This expertise will help shape the infrastructure, tooling, feature and data systems, APIs, and operational standards that enable MLEs to reliably move models from development into production. As League’s senior Tech Lead for ML platform and integrations, the role also includes driving strategy and adoption across teams, leading year-plus initiatives spanning multiple products, and mentoring senior ML Engineers while helping shape how League builds and evolves player- and developer-facing ML experiences. The position reports to the Senior ML Engineering Manager within the League of Legends game team and is based out of our Los Angeles headquarters. Responsibilities: Lead AI/ML workflow and MLOps for League of Legends; set automation standards including auto-remediation and self-healing pipelines; drive implementation. Lead AI/ML serving architecture that scales to production load for Riot’s player base; design systems requiring minimal operational intervention; drive implementation of proven serving architectures. Lead ML feature platform in partnership with data engineering to scale feature development and processing; solve scale, latency, or reliability constraints in ML data pipelines. Lead AI/ML developer experience that accelerates development; remove workflow bottlenecks and enable new capabilities. Lead AI/ML governance in partnership with compliance experts to ensure regulatory adherence; drive implementation of proven frameworks. Lead AI/ML platform security in partnership with security teams; drive implementation of proven privacy, security, and cryptography techniques for AI/ML. Drive AI/ML pipeline development and deployment standards, coordinating with data engineering on shared MLOps capabilities. Drive AI/ML service development and API standards across product integrations. Drive operational excellence and cost optimization for AI/ML systems across the organization. Drive incident management and response standards for AI/ML systems across production services. Drive observability and monitoring standards for AI/ML systems across services. Drive tooling strategy and evaluation for AI/ML platforms across the organization. Drive mentorship of senior engineers across multiple products or problem areas; coach developers across disciplines. Drive recruiting standards across multiple products or problem areas; contribute to interview kits and TA efforts. Qualifications: Bachelor’s degree in Computer Science or a related field, or equivalent practical experience. 10+ years of professional software engineering experience, including 5+ years building production ML platforms, systems, or MLOps capabilities. Evidence that platforms or systems you’ve led have become load-bearing for multiple teams or products — adopted, depended on, and evolved beyond the original scope. Deep operational intuition for ML systems at scale: you’ve lived through the failure modes (training-serving skew, silent degradation, cost spirals) and built the systems to prevent them. Background in cloud-native orchestration and large-scale system design (Kubernetes, GPU scheduling, container orchestration) applied at global scale. History of improving developer experience for ML practitioners in ways that measurably changed how fast or reliably they shipped. Track record mentoring senior and staff-level engineers; evidence of elevating platform engineering judgment across an organization. Experience building ML platforms that serve multiple products or game titles simultaneously is a plus. Track record solving novel scale, latency, or reliability constraints in ML data pipelines is a plus. Background in ML governance, security, privacy-preserving techniques, or compliance at organizational scale is a plus. Passion for player experience, games, or creative technology. For this role, you will find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role! 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

The position reports to the Senior ML Engineering Manager within the League of Legends game team and is based out of our Los Angeles headquarters.
Lead AI/ML workflow and MLOps for League of Legends; set automation standards including auto-remediation and self-healing pipelines; drive implementation.
Lead AI/ML serving architecture that scales to production load for Riot’s player base; design systems requiring minimal operational intervention; drive implementation of proven serving architectures.
Lead ML feature platform in partnership with data engineering to scale feature development and processing; solve scale, latency, or reliability constraints in ML data pipelines.
Lead AI/ML developer experience that accelerates development; remove workflow bottlenecks and enable new capabilities.
Lead AI/ML governance in partnership with compliance experts to ensure regulatory adherence; drive implementation of proven frameworks.
Lead AI/ML platform security in partnership with security teams; drive implementation of proven privacy, security, and cryptography techniques for AI/ML.
Drive AI/ML pipeline development and deployment standards, coordinating with data engineering on shared MLOps capabilities.
Drive AI/ML service development and API standards across product integrations.
Drive operational excellence and cost optimization for AI/ML systems across the organization.
Drive incident management and response standards for AI/ML systems across production services.
Drive observability and monitoring standards for AI/ML systems across services.
Drive tooling strategy and evaluation for AI/ML platforms across the organization.
Drive mentorship of senior engineers across multiple products or problem areas; coach developers across disciplines.
Drive recruiting standards across multiple products or problem areas; contribute to interview kits and TA efforts.
Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.
10+ years of professional software engineering experience, including 5+ years building production ML platforms, systems, or MLOps capabilities.
Evidence that platforms or systems you’ve led have become load-bearing for multiple teams or products — adopted, depended on, and evolved beyond the original scope.
Deep operational intuition for ML systems at scale: you’ve lived through the failure modes (training-serving skew, silent degradation, cost spirals) and built the systems to prevent them.
Background in cloud-native orchestration and large-scale system design (Kubernetes, GPU scheduling, container orchestration) applied at global scale.
History of improving developer experience for ML practitioners in ways that measurably changed how fast or reliably they shipped.

Nice-to-haves

Experience building ML platforms that serve multiple products or game titles simultaneously is a plus.
Track record solving novel scale, latency, or reliability constraints in ML data pipelines is a plus.
Background in ML governance, security, privacy-preserving techniques, or compliance at organizational scale is a plus.

Application prep

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

Keywords to mirror

mlmachine learningaidesign systemsapikubernetes

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto

Paid Time Off

Parental Leave