Mahesh Murag
About Mahesh Murag
Mahesh Murag is a Product Manager at Tecton, where he has worked since 2023, focusing on data challenges in machine learning for real-time applications. He holds a Bachelor of Science in Electrical Engineering and Computer Science from the University of California, Berkeley, and has previously held positions at Stanford University, Scale AI, and other tech companies.
Work at Tecton
Mahesh Murag has been serving as a Product Manager at Tecton since 2023. In this role, he focuses on addressing data challenges in machine learning for real-time applications. He is the third Product Manager to join the team, contributing to Tecton's mission of enhancing machine learning capabilities for enterprise-level applications. Tecton is supported by prominent investors such as Sequoia Capital, Andreessen Horowitz, and Kleiner Perkins.
Education and Expertise
Mahesh Murag earned a Bachelor of Science in Electrical Engineering and Computer Science (EECS) from the University of California, Berkeley. His educational background provides a strong foundation for his work in product management and engineering, particularly in the fields of machine learning and software development.
Background
Mahesh Murag completed his secondary education at Monta Vista High School before pursuing higher education at UC Berkeley. His early academic achievements laid the groundwork for his subsequent career in technology and product management. He has gained diverse experience through various internships and research positions.
Professional Experience
Prior to his current role at Tecton, Mahesh Murag worked as a Product Manager at Scale AI from 2021 to 2023, focusing on eCommerce. He also held several research and internship positions, including roles at Stanford University, Quizlet, Lyft, Microsoft, and RackWare Inc. His experience spans research, software engineering, and product management, contributing to his expertise in the tech industry.
Research Contributions
Mahesh Murag has contributed to research initiatives at Stanford University and Berkeley Artificial Intelligence Research. His research roles included positions as a researcher at Stanford in 2015 and 2016, and at Berkeley from 2018 to 2019. These experiences have enhanced his understanding of artificial intelligence and its applications in real-world scenarios.