Rajat Tripathi

Software Engineer at Pinecone

New York, New York, United States
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Summary

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Rockstar
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Top School
Rajat Tripathi is a software engineer based in New York with 11 years of experience building data-driven and cloud-native systems, currently contributing to data and platform efforts at Pinecone. He combines deep practical expertise in Rust and Kubernetes with hands-on ML and data engineering—evidenced by his work on Jupyter-based deduplication and threat-detection notebooks for Pinecone’s examples repo. His background spans platform engineering, CI/CD tooling, and AIOps, plus applied ML from a Boston University MS in Artificial Intelligence. Rajat has mentored over 60 students in computer vision topics and delivered ML solutions for NGOs, academia, and government, reflecting both technical depth and strong knowledge transfer skills. Colleagues rely on him to bridge research prototypes and production-grade systems, especially where vector databases and scalable orchestration intersect.
code11 years of coding experience
job4 years of employment as a software developer
bookHigh School, Science, High School, Science at Jamshedpur Public School
bookBachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Manipal Institute of Technology
bookMaster of Science - MS, Artificial Intelligence, Master of Science - MS, Artificial Intelligence at Boston University
languagesEnglish, German
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Github Skills (5)

jupyter-notebook10
vector-database10
python10
ai9
llm8

Programming languages (11)

TypeScriptJavaDockerfileRustSCSSScalaTeXJavaScript

Github contributions (5)

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pinecone-io/examples

Apr 2021 - Feb 2022

Jupyter Notebooks to help you get hands-on with Pinecone vector databases
Role in this project:
userFull-stack Developer
Contributions:11 reviews, 80 commits, 60 PRs in 10 months
Contributions summary:Rajat released a "dedup,q & a" functionality and updated the quick tour, indicating involvement in multiple areas. They worked on deduplication of scholarly articles using Jupyter Notebooks, which involves data processing and machine learning. The user also added an IT threat detection notebook, signifying responsibility for feature implementation.
aijupyter-notebookllmpythonsemantic-search
Contributions:2 commits, 1 push, 1 branch in 1 day
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