Top expert inNatural Language Processing and Machine Learning Technologies
Hai Jin is a software leader and co-founder with 8 years of industry experience building cloud-native and vector search systems from Shanghai. He co-created Milvus and Infinity projects and now leads InfiniFlow, combining hands-on full-stack development with platform-level backend expertise in high-performance databases and RAG engines. His open-source contributions span Milvus, MatrixOne, and the RAGFlow engine, showing deep familiarity with C++/Rust backend internals, APIs, and developer-facing SDKs. Prior roles as VP of Engineering at MatrixOrigin and Director of Engineering at Zilliz reflect a track record of scaling teams and production systems for cloud and edge-native data platforms. Trained in electrical and electronics engineering at Shanghai Jiao Tong University, he blends systems-level rigor with practical product delivery and a knack for refactoring complex codebases into maintainable, documented projects.
8 years of coding experience
16 years of employment as a software developer
Bachelor of Science - BS, Electrical, Electronics and Communications Engineering, Bachelor of Science - BS, Electrical, Electronics and Communications Engineering at Xidian University
Master of Science - MS, Electrical and Electronics Engineering, Master of Science - MS, Electrical and Electronics Engineering at Shanghai Jiao Tong University
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Role in this project:
Back-end Developer
Contributions:29 releases, 56 reviews, 1699 commits in 1 year 8 months
Contributions summary:Hai's commits focus on the implementation of backend features, including adding new APIs, and enhancing existing functionalities. These commits involve modifications in `cpp` files, suggesting a strong emphasis on server-side logic and interactions within the Milvus vector database. The code changes touch upon index creation, get vector ID by ids, and other essential functions.
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
Role in this project:
Full-stack Developer
Contributions:10 releases, 273 reviews, 284 PRs in 1 year
Contributions summary:Hai primarily contributed to the development of RAGFlow, demonstrating proficiency in both backend and frontend development. Their work includes setting up an Actix web template, updating language settings in the API and frontend, and refactoring various backend functionalities. The user also focused on documentation updates, adding a license, and refactoring the API.
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