Director, Machine Learning Engineering - AI Foundations

Riot Games•Los Angeles, CA

3h•$321,100 - $482,200

About The Position

Riot is building the capabilities to move AI and machine learning from promise and prototype into reliable production systems. AI Foundations builds shared platforms and enables teams across Riot to deliver meaningful AI-powered outcomes. The Director, Machine Learning Engineering oversees the AI Foundations engineering organization and is accountable for its technical impact, organizational health, operational excellence, software and machine learning craft quality, and engineering output. All Engineering Managers in AI Foundations report to this role. The director partners with product and executive leaders to connect Riot’s goals to a clear charter, long-term roadmap, and investment choices. This organization-level leader stays technically engaged to understand engineering realities, guide important decisions, and address risks while enabling managers and teams to lead execution. The role involves setting technical strategy, developing engineering managers, owning the outcomes of multiple teams, planning organizational capabilities, guiding technical quality and operational ownership, improving organizational processes, creating leverage across Riot, and communicating decisions and risks clearly. The position calls for strong player empathy and a personal relationship with games, alongside craft expertise and a collaborative spirit.

Requirements

12+ years of industry experience in software engineering, machine learning engineering, AI, or a closely related discipline, including 8+ years of management experience.
Proven ability to coach managers, set clear expectations, manage performance, develop future leaders, maintain a high and consistent engineering bar, and be accountable for organization-wide outcomes.
Strong record of building, shipping, and operating production software, AI/ML systems, or platforms that deliver measurable value to players, customers, or internal teams.
Strong technical credibility and judgment across software systems and AI/ML, including ability to assess architecture, quality, operational health, reliability, scale, security, cost, and user impact and guide technical direction across teams.
Demonstrated ability to turn ambiguous product or business needs into an organizational strategy, long-term roadmap, measurable outcomes, and clear priorities; make trade-offs based on mission, capacity, and impact; and maintain alignment as plans change.
Experience shaping organizational capacity and capabilities, including identifying skills gaps, planning staffing, and making sound hiring and investment decisions.
Demonstrated ability to build trust and influence across organizational boundaries, including with product, game, platform, data, research, and executive partners.
Excellent written and verbal communication, with a bias toward clarity, explicit ownership, timely feedback, and candid discussion of uncertainty.
Sound judgment around responsible AI and production risk, including privacy, security, safety, and the operational consequences of deploying AI-enabled systems.
Experience in live-service games, interactive entertainment, consumer products, or other high-scale, real-time environments.
Experience in one or more areas such as generative AI, LLM applications, agentic systems, personalization, recommendations, ranking, player modeling, game AI, reinforcement learning, computer vision, or multimodal systems.
Bachelor’s degree in Computer Science, Engineering, Machine Learning, or a related field, or equivalent practical experience.

Nice To Haves

Experience partnering across data engineering and platform teams on model development and operations, including data and feature pipelines, inference services, orchestration, model registries, evaluation, or ML observability.
Experience building AI/ML products, shared platforms, developer tools, or technical capabilities used by multiple product groups.
Graduate degree in Computer Science, Engineering, Machine Learning, or a related field.

Responsibilities

Set technical strategy and direction; shape AI Foundations’ charter, priorities, and long-term roadmap with product and engineering partners.
Translate organizational goals into clear outcomes, make investment and trade-off decisions, and clarify what the organization will and will not take on.
Lead and develop the engineering management organization by setting expectations, coaching managers, maintaining a consistent management and performance bar, and developing future leaders.
Own the output and outcomes of multiple teams; ensure goals and value are understood, evaluate commitments against the roadmap, make delivery and risks visible, and unblock or accelerate work as needed.
Plan future staffing and skills, identify capability gaps, develop role or team proposals, and partner with Talent on hiring and onboarding.
Make hiring decisions at the appropriate level and drive strategic planning, forecasting, and compensation planning for the organization.
Guide technical quality and operational ownership across AI/ML, software, data, and agentic systems.
Build alignment on architecture and technical strategy and ensure reliable, secure, maintainable production systems with appropriate evaluation, observability, incident response, and ownership.
Make trade-offs across quality, reliability, latency, cost, and technical sustainability.
Improve organizational efficiency, team health, and delivery transparency; address recurring friction, misalignment, and unresolved risks, and ensure the organization learns from operational issues.
Build trusted partnerships across game teams and central functions and share reusable engineering patterns, platform capabilities, evaluation approaches, and lessons learned across Riot.
Communicate decisions, trade-offs, and uncertainty clearly; surface risks early, provide timely and actionable feedback, and resolve difficult conversations with candor and sound judgment.