Tevin Wang
Member Of Technical Staff (Intern) at OpenAI
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolTevin Wang is a Carnegie Mellon computer science student and pragmatic software engineer with seven years of hands-on experience building back-end systems, testing infrastructure, and developer tooling for AI-focused projects. He has interned at OpenAI, Pinecone, LanceDB (YC W22) and Chess.com, contributing production-ready CI/CD, Rust and Python implementations, and a node SDK build process to improve reliability and developer experience. At LanceDB he helped ship features for vector/embedded retrieval and authored “critique-based contexting” for reducing LLM hallucinations, bridging researchy ideas with practical integrations (OpenAI, Vercel). Based in San Francisco, Tevin combines interest in web dev, design, and startups with a knack for making documentation and automation executable and testable—an often-overlooked but impactful area in developer-facing projects.
7 years of coding experience
1 year of employment as a software developer
AMSE Artist Business and Entrepreneurship, AMSE Artist Business and Entrepreneurship at Valley Christian HighBachelor of Science - BS Computer Science, Bachelor of Science - BS Computer Science at Carnegie Mellon University
English, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (8)
github-ci10
javascript10
githubaction-workflow10
python10
cicd10
documentation9
approximate-nearest-neighbor-search5
vector-database4
Programming languages (13)
Github contributions (5)
lancedb/lancedb
May 2023 - Aug 2023
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:16 reviews, 17 PRs, 47 pushes in 3 months
Contributions summary:Tevin contributed to the project by adding and configuring testing infrastructure and automation for the documentation build process. They implemented a Python testing framework, along with JavaScript testing scripts. Additionally, the user made modifications to the repository's documentation to ensure the code examples were runnable and integrated with the testing framework. Furthermore, they introduced changes for building the node SDK within the release process.
approximate-nearest-neighbor-searchimage-searchnearest-neighbor-searchrecommender-systemsearch-engine
TevinWang/me
Jun 2020 - Sep 2022
Contributions:23 pushes, 1 branch in 2 years 4 months
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