Ian Schweer
About Ian Schweer
Ian Schweer is a Staff Software and Machine Learning Engineer at Riot Games, where he has worked since 2020. He has a background in software engineering with experience at companies such as Adobe, DoorDash, and ActiveLAMP, and holds a Bachelor's Degree in Computer Science from UC Irvine.
Work at Riot Games
Ian Schweer has been employed at Riot Games since 2020, serving as a Staff Software + Machine Learning Engineer. His role involves developing advanced machine learning models and software solutions for the League of Legends Game Engine. Notable projects include the development of a Neural Network processing engine and the automation of PyTorch torchscript integration with the League of Legends Content Authoring system. He also authored telemetry standards to capture game state and actions within the game.
Previous Experience in Software Engineering
Prior to his tenure at Riot Games, Ian Schweer worked at Adobe as a Software Engineer from 2015 to 2018. He later transitioned to a role at DoorDash as a Software Engineer focused on Data Platform from 2019 to 2020. Additionally, he held positions at ActiveLAMP as a Full Stack Engineer from 2012 to 2014 and at Excelsior, A Public Charter School as a Software Engineer from 2014 to 2015. His experience spans various aspects of software development and data engineering.
Educational Background in Computer Science
Ian Schweer pursued his education in Computer Science at Victor Valley College, where he achieved a Bachelor of Applied Science (B.A.Sc.) from 2011 to 2013. He furthered his studies at UC Irvine, obtaining a Bachelor's Degree in Computer Science from 2014 to 2017. His academic background laid the foundation for his career in software engineering and machine learning.
Technical Skills and Contributions
Ian Schweer has demonstrated expertise in machine learning and software engineering through various contributions. He ported metagame analysis models to the Spark MLlib stack, utilizing techniques such as latent Dirichlet allocation and Hierarchical Logistic Regression. His work reflects a strong proficiency in integrating machine learning techniques within gaming environments.