Jai Chopra
Senior Product Manager at Uber
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJai Chopra is a Senior Product Manager in San Francisco with a decade of experience building AI-first products and platforms, currently leading multimodal AI efforts at Uber. He was the first product hire and Head of Product at LanceDB (YC W22), where he helped pivot and take a developer-focused vector/multimodal database from 0 to 1 and contributed code and examples that integrate LanceDB with LangChain and OpenAI. Prior to that he led technical product teams at Cruise focused on perception, prediction, and ML/platform tooling, combining hands-on engineering background with product strategy. With an MS in Computer Science and early startup founding and CTO experience, he blends founder grit, full-stack development chops, and a track record of shipping infrastructure that powers real-world AI applications. An understated strength is his ability to move fluidly between shipping code and shaping developer-facing product journeys, evidenced by active contributions to an open-source AI retrieval stack.
10 years of coding experience
12 years of employment as a software developer
Y CombinatorThe University of SydneyUNSW Sydney
Github Skills (11)
pandas10
vector-database10
openai10
python10
langchain10
semantic-search10
natural-language-processing9
approximate-nearest-neighbor-search9
nlp9
machine-learning8
ml8
Programming languages (4)
Github contributions (5)
lancedb/lancedb
Feb 2023 - Aug 2023
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:11 reviews, 49 PRs, 47 pushes in 5 months
Contributions summary:Jai contributed to the development of a question-and-answer bot using LangChain and LanceDB, demonstrating skills in integrating these technologies. Their commits included adding an example Q&A bot using the Pandas documentation, integrating with OpenAI, and implementing the retrieval of answers to queries. The user also updated documentation and examples, and refactored existing code.
approximate-nearest-neighbor-searchimage-searchnearest-neighbor-searchrecommender-systemsearch-engine
jaichopra/ai-product-hackathon
Jun 2023 - Jun 2023
Documentation and starter code for the 2023 AI x Product Hackathon
Contributions:5 pushes in 1 day
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