Parth Gupta
Director, Search & Discovery at Coupang
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolParth Gupta is a search and machine learning leader with 15 years of experience building large-scale relevance, ranking and discovery systems across Amazon and now Coupang. He has led cross-functional teams to deliver measurable business impact—owning dynamic bidding for Amazon Ads and driving new product discovery that generated multi-hundred-million-dollar uplift—while also shipping low-latency online modules to solve cold-start for new products. Technically grounded as an applied scientist and PhD-trained researcher, he bridges research and engineering, with contributions to learning-to-rank in the Xapian search engine and production ML systems like image-embedding pipelines for catalog similarity. Based in the Bay Area, he combines a strategic product roadmap mindset with hands-on code-level expertise in search internals and LETOR integrations. A recurring theme in his career is turning novel research (cross-view embeddings, query intent modeling) into robust, high-throughput services that scale globally.
14 years of coding experience
6 years of employment as a software developer
Master of Technology (M.Tech.) Computer Science, Master of Technology (M.Tech.) Computer Science at Dhirubhai Ambani Institute of Information and Communication TechnologyUniversitat Politècnica de València
Github Skills (9)
c-language10
cprogramming-language10
xapian10
machine-learning9
refactoring8
data-structure7
data-structures7
algorithm7
algorithms7
Programming languages (3)
Github contributions (5)
xapian/xapian
May 2011 - Jun 2012
Mirror of the Xapian repository. You're welcome to open pull requests on github (they'll just get merged indirectly).
Role in this project:
Back-end Developer
Back-end DeveloperContributions:31 commits, 12 comments in 1 year
Contributions summary:Parth's commits indicate a focus on the Xapian search engine's internal architecture. The primary contribution appears to be refactoring and connecting various internal components, specifically `featuremanager.cc`, `featurevector.cc`, and `letor_internal.cc`, to support machine learning ranking capabilities. This involved modifying existing code and introducing new features related to relevance calculations and training file preparation. The user's work directly impacted the integration of LETOR (Learning to Rank) functionality within the Xapian framework.
mergedpull-requestsxapianwelcome
parthg/clpd-kbs
Apr 2014 - Nov 2016
Contributions:8 commits, 1 push in 2 years 8 months
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