Hari Malladi

Hari Malladi is a Full Stack Developer at Scale AI since May 2024, where responsibilities include designing and implementing scalable back-end systems for AI applications and developing RESTful APIs for high-volume data processing. Previously, as an Undergraduate Research Assistant at Purdue Physics and Astronomy, Hari developed a method for embedding quadratic unconstrained binary optimization problems on a quantum annealer for use in CERN's CMS experiment. Earlier experience includes a Business Development Internship at Numbers Only, Inc. Hari Malladi is pursuing a Bachelor of Science degree in Mathematics and Physics at Purdue University, expected to graduate in 2024.