Nikhil Y.
About Nikhil Y.
Nikhil Y. is a Staff Software Engineer at ThoughtSpot, where he has worked since 2023. He has extensive experience in software engineering, having held various technical roles at ThoughtSpot and other companies, and has a strong academic background in computer science.
Work at ThoughtSpot
Nikhil Y. is currently employed as a Staff Software Engineer at ThoughtSpot, a position he has held since 2023 in Mountain View, California. His career at ThoughtSpot began in 2019, where he served in various technical roles, including Member of Technical Staff 2, Member of Technical Staff 4, and Senior Member of Technical Staff. Throughout his tenure, he has contributed to significant projects, such as implementing an ad-hoc formula and query generation using natural language, which infers SQL from large language models (LLM). He leads a team of nine engineers across two time zones, overseeing three core services.
Education and Expertise
Nikhil Y. holds a Master of Science (MS) in Computer Science from the University of Massachusetts Amherst, where he studied from 2017 to 2018. Prior to that, he earned a Bachelor of Technology (B.Tech.) in Computer Science from the Indian Institute of Technology, Delhi, completing his degree from 2011 to 2015. His educational background has equipped him with a strong foundation in software engineering and technical problem-solving.
Background
Before joining ThoughtSpot, Nikhil Y. gained experience in various roles across different organizations. He worked as a Graduate Researcher at the University of Massachusetts Amherst in 2018 and held multiple positions at Barclays Investment Bank, including Summer Analyst and Business Analyst. He also worked at Samsung Electronics as a Software Engineer and interned there as a Software Engineering Intern. His early career included a role as a Research Engineer at Bobble Keyboard.
Achievements
Nikhil Y. has made notable contributions during his career, particularly at ThoughtSpot. He developed a multi-level semantic cache to optimize costs and reduce latency for API calls to LLM services. Additionally, he collaborated with metadata teams to transition single-tenant services to a multi-tenant architecture as part of the firm's NorthStar initiative. He led the ideation and implementation of a feedback incorporation mechanism that improved the accuracy of Natural Language Search to 95%, as reported by customers.