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Hebo Yang is a Machine Learning Infra Engineer at DoorDash, focusing on building machine learning tooling and infrastructure since 2020. Prior to this role, Hebo served as an Applied Machine Learning Engineer at Microsoft, contributing to the development of an anomaly detection system on Spark, and as a Software Engineer, where responsibilities included working on Azure Resource Manager for distributed systems. Earlier experience includes a Technology Analyst position at Bank of America, developing real-time distributed systems, and a Summer Analyst role at Bank of America/Merrill Lynch, creating frameworks for managing reference data. Hebo's career also includes positions such as Analyst Intern at Institutional Life Services, Research Assistant at Columbia University, and Summer Intern at Deutsche Boerse AG, alongside a teaching assistantship at the University of Illinois at Urbana-Champaign. Academically, Hebo holds a Master's degree in Mathematics of Finance & Computer Science from Columbia University and a Bachelor's degree in Actuarial Science and Computer Science from the University of Illinois Urbana-Champaign.