Director, Machine Learning Engineering - AI Foundations

The opportunity

Riot is building the capabilities to carry AI and machine learning from promise, through prototype, into reliable production systems. AI Foundations helps make that possible by building shared platforms and enabling teams across Riot to deliver meaningful AI-powered outcomes.

We are looking for an engineering leader to oversee the AI Foundations engineering organization. You will be accountable for the technical impact of the group including organizational health, operational excellence, software and machine learning craft quality, and engineering output. All Engineering Managers in AI Foundations will report into this role.

You will partner with product and executive leaders to connect Riot’s goals to a clear charter, long-term roadmap, and investment choices. The role calls for an organization-level leader who stays technically engaged: close enough to understand the engineering realities, guide important decisions, and address risks, while creating the clarity and space for managers and teams to lead execution.

Responsibilities:

Set technical strategy and direction. Work with product and engineering partners to shape AI Foundations’ charter, priorities, and long-term roadmap. Translate organizational goals into clear outcomes, make deliberate investment and trade-off decisions, and explain what the organization will and will not take on.

Lead and develop the engineering management organization. Set clear expectations, coach managers to take ownership and deliver results, uphold a consistent engineering-management and performance bar, and identify and develop future leaders.

Own the organization’s results. Be accountable for the total output and outcomes of multiple teams. Ensure teams understand their goals and value, evaluate commitments against the roadmap, make delivery and risks visible, and act quickly to unblock or accelerate work when needed.

Build the organization and its capabilities. Plan for future staffing and skills, identify gaps against the roadmap, and develop role or team proposals grounded in opportunity and cost. 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. Stay engaged in the technical outcomes across AI/ML, software, data, and agentic systems. Build alignment on architecture and technical strategy; ensure teams deliver reliable, secure, maintainable production systems with appropriate evaluation, observability, incident response, and ownership. Make sound trade-offs across quality, reliability, latency, cost, and technical sustainability.

Improve how the organization works. Build operating mechanisms that improve efficiency, team health, and delivery transparency. Address recurring friction, misalignment, and unresolved risks directly. Ensure the organization learns from operational issues and changes course as needed.

Create leverage across Riot. Build trusted partnerships across game teams and central functions. Share reusable engineering patterns, platform capabilities, evaluation approaches, and lessons learned so AI Foundations’ work strengthens Riot’s ability to build and operate AI systems beyond any one team.

Communicate with clarity. Make decisions, trade-offs, and uncertainty legible to managers, engineers, product partners, game leaders, and executives. Surface risks early, give timely and actionable feedback, and resolve difficult conversations with candor and sound judgment.

Required Qualifications:

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, and maintain a high and consistent engineering bar with accountability for organization-wide outcomes.

A 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—sufficient to assess architecture, quality, operational health, reliability, scale, security, cost, and user impact, and to guide technical direction across teams.

Demonstrated ability to turn ambiguous product or business needs into an organization 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 with 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.

Desired Qualifications:

Experience partnering across data engineering and platform teams on model development and operations, including data and feature pipelines, inferen…