About the company
Riot Games is a game company that puts players first. Our mission drives every decision in our quest to create games and experiences that make it better to be a player.
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
Requirements
- 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
Conditions
- Open paid time off policy and other perks such as flexible work schedules
- Medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match