John Jung
About John Jung
John Jung serves as the VP of Engineering at Nylas, where he leads machine learning teams specializing in natural language processing, computer vision, and deep learning. He has a strong background in building engineering teams and has held various leadership roles in technology and research organizations.
Current Role at Nylas
John Jung serves as the VP of Engineering at Nylas, a position he has held since 2022. In this role, he focuses on leading engineering initiatives and fostering a team environment that emphasizes psychological safety and creativity. His leadership is instrumental in driving the development of innovative solutions within the company.
Previous Experience at Nylas
Prior to his current role, John Jung worked at Nylas as the Senior Director of Engineering from 2020 to 2022. His responsibilities included overseeing engineering projects and contributing to the company's technological advancements. Before that, he co-founded June.ai, which was acquired by Nylas, and served as its CTO from 2016 to 2020.
Expertise in Machine Learning and AI
John Jung possesses expertise in leading machine learning teams with a focus on natural language processing (NLP), computer vision, and deep learning. His work involves applying AI and machine learning techniques, including large language models, to enhance email and calendar applications, contributing to the evolution of these technologies.
Research Background
John Jung has a solid research background, having worked at NYU Langone Medical Center as a researcher for four months in 2011. He also spent three years at the University of Rochester Medical Center from 2009 to 2012, where he contributed to various research projects. Additionally, he worked at NASA Goddard Space Flight Center and the University of Maryland from 2003 to 2007, focusing on cosmic ray energy and mass.
Educational Qualifications
John Jung studied at the Rochester Institute of Technology, where he earned a Bachelor of Science degree in Biomedical Sciences from 2007 to 2009. His educational background provides a foundation for his work in engineering and research, particularly in the fields of AI and machine learning.