Staff Machine Learning Engineer, Animation - Singapore Efficiency Team

Riot Games was established in 2006 by entrepreneurial gamers who believe that player-focused game development can result in great games. In 2009, Riot released its debut title League of Legends to critical and player acclaim. As the most played PC game in the world, over 100 million play every month. Players form the foundation of our community and it’s for them that we continue to evolve and improve the League of Legends experience. We’re looking for humble but ambitious, razor-sharp professionals who can teach us a thing or two. We promise to return the favor. Like us, you take play seriously; you’re passionate about games. We embrace those who see things differently, aren’t afraid to experiment, and who have a healthy disregard for constraints. That's where you come in. Riot’s Singapore Efficiency team builds the technology that lets our creative teams do their best work. Animation carries some of the most time-consuming technical work in the studio, including retargeting, cleanup, foot-locking, and rig wrangling, and this role is about taking that load off animators so they can spend more time on performance and expression. You will be reporting to the Sr Manager, Machine Learning Engineer. As a Staff Machine Learning Engineer, Animation , you’ll design and ship ML tools that accelerate the technical scaffolding around animation, from motion processing to rig-related workflows, and integrate them into the way animators already work.

What you'll do

Build assistive animation tooling, drawing on motion synthesis, motion matching/blending, retargeting, and physics-based character control, to remove mechanical steps from the animator’s workflow.
Partner with animators and tech artists to target costly keyframing, cleanup, and retargeting work and ship tooling that shortens it.
Define and run evaluations for motion quality (naturalness, foot-sliding, responsiveness) and quantify the time returned to animators.
Follow developments in motion generation and character control and judge what holds up on production rigs and within runtime budgets.

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