League of legends faces lots of interesting problems in the data space that are unique due to the video game aspect. How do you deploy and train models in a binary video game? How has the data and ML stack changed since the league's inception in 2009? How do you do player-facing ML (Lane detection, feeding detection, etc.) and decision science at this scale?
Ian is a senior software engineer at Riot Games, working on the League Data Central team. Along with his team, Ian ships Machine Learning and Data products to millions of league of legends and tft players including in game recommendations, player behavior models, and internal decision science to help make the game a better place for all. Ian has worked on large data systems at Adobe and Doordash before coming to Riot Games. In his free time, he plays in metal bands and hangs out with his 2 year old daughter.