Sr. Manager, Machine Learning Engineering - Game Tech Group, AI Foundations

Riot Games•Los Angeles, CA

12h

About The Position

Engineering managers at Riot are technical leaders first — they stay close to the craft, make grounded architectural decisions, and earn credibility through the quality of their technical judgment. They are also deeply invested in people: building diverse teams, growing individual careers, and creating environments where engineers do the best work of their lives. The best Riot engineering managers hold both of these responsibilities without trading one for the other. AI Foundations (AIF) designs and operates Riot's production execution layer for models, agents, and AI-native workflows. The organization has three teams: ML Platform (model hosting, inference, lifecycle tooling), ML Bots (game-agent runtime and training), and Production AI (AI developer workflows, tooling, and vendor management), plus a small leadership staff. Together, these teams serve every game studio and central team at Riot that wants to use AI. As the Senior Manager, ML Engineering for AI Foundations, you will lead the group's engineering managers and a set of senior ICs, owning the organization's mid-term (~1 year) technical and capability roadmap. You will be accountable for coherent engineering practice across the three sub-teams, for the group's combined delivery against strategic commitments, and for building the kind of engineering culture that attracts and retains strong ML talent. This is a servant-leadership role on a team full of servant leaders. You succeed when frontline managers have the context they need to lead, senior ICs have room to focus, and teams across Riot can adopt AI with confidence. You will partner with peer leaders in game studios and central teams to understand their AI adoption challenges and feed those patterns back into the platforms and tools your teams build. You will report to the Director of AI Foundations.

Requirements

BS in Computer Science, Machine Learning, or related field (or equivalent experience); 10+ years of industry experience including experience as a Senior ML Engineer or higher.
4+ years of management experience, including managing managers or team leads. Track record of building engineering culture by enabling the people around you.
Evidence of shipping production ML systems that other teams depend on, with real operational weight. Working knowledge of model serving, CI/CD for ML, observability, and cost tradeoffs even if you're not writing code daily.
Experience translating technical vision into a roadmap your teams executed against, with evidence of course-correcting when priorities shifted.
Strong collaboration across ML, platform, product, and game development teams; track record of alignment across org boundaries. Experience making AI accessible to teams without deep ML expertise

Nice To Haves

For this role, you'll 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!

Responsibilities

Own the group's mid-term (~1 year) capability roadmap and 1+ year technical strategy; balance investment across custom platforms and tool adoption based on where Riot gets the most value.
Track adoption and impact metrics; re-prioritize based on usage data and partner feedback.
Ensure coherent technical direction across sub-teams; connect local tech strategy to Riot's broader AI direction. Contribute to architecture discussions, code when it helps, and support design cross-team decisions.
Set a high bar for craft, operational rigor, and continuous learning; codify and share best practices for production ML (serving, MLOps, observability, responsible AI) so lessons from one team benefit all.
Establish shared operational practices including cross-team on-call; maintain high ML system and model quality; ensure adherence to Responsible AI standards including fairness, explainability, and safety.
Manage MLE team leads and senior ICs; coach managers to maintain a high performance bar and build growth plans.
Develop ML engineering leaders; mentor ICs into management or senior technical roles; drive promotions at the Staff and Principal levels.
Align staffing against AIF priorities, development goals, and career paths; own headcount requests (FTE and contractor). Partner with the talent team; set staffing priorities for technical roles in AIF; work with hiring managers around Riot to improve hiring practices for AI-related roles.
Work with AIF leadership to establish operational and tooling budgets, including training, travel, and conference investment.
Build alignment with game studios, central tech teams, and vendor partners; identify and de-risk dependencies. Manage AI vendor relationships (evaluation, integration, ongoing partnership) in coordination with AIF leadership.
Make the transition from Tech Research to production repeatable, with clear handoff practices so promising research reaches players and Rioters.
Advocate for AI-native workflows within AIF and across Riot; ensure stakeholders know what AIF is building, why, and how to engage. Make grounded build-vs.-adopt recommendations.
Encourage teams to share what they learn — write-ups, demos, reusable components — so others across Riot can adopt AI more easily.