Li Liu
Director Of Engineering at Zilliz
Redwood City, California, United States
Summary
🤩
Rockstar🎓
Top SchoolLi Liu is a Director of Engineering based in Redwood City with four years of focused experience leading vector search and cloud-native database engineering. At Zilliz he progressed from Staff to Principal to Director, driving Milvus development and leading teams that scale high-performance vector ANN search systems. His background includes building stream processing and ad-accounting systems at Meta and distributed data warehousing at Autonomic, giving him strong production experience across low-latency, data-intensive platforms. An active contributor to the Milvus open-source project, he has fixed core segment bugs, optimized bitset checks, and upgraded key dependencies to boost performance and stability. Li combines hands-on back-end optimization with people leadership, and his work reveals a practical knack for squeezing efficiency from complex, high-throughput systems.
3 years of coding experience
6 years of employment as a software developer
Tianjin UniversityMaster Information Technology, Master Information Technology at Carnegie Mellon University
Chinese, English
Github Skills (15)
golang10
nearest-neighbor-search10
vector-search10
vector-database10
develop10
go10
backend10
nearest-neighbors10
bitset9
cprogramming-language9
c-language9
hnswlib9
databases8
database8
faiss8
Programming languages (6)
Github contributions (5)
milvus-io/milvus
Sep 2022 - Jan 2023
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Role in this project:
Back-end Developer
Back-end DeveloperContributions:236 reviews, 16 commits, 55 PRs in 3 months
Contributions summary:Li contributed to the Milvus vector database project by fixing bugs, optimizing code, and upgrading dependencies. They addressed a mis-copy issue in the core segment implementation. Furthermore, they improved efficiency by leveraging the `all()` API for bitset checks and optimizing low-efficient code within core functionalities. The user also upgraded external dependencies, such as Knowhere, to newer versions to improve performance and stability.
approximate-nearest-neighbor-searchfaisshnswsimilarity-searchvector
liliu-z/milvus
Sep 2022 - Mar 2025
Vector database for scalable similarity search and AI applications.
Contributions:61 pushes, 84 branches, 1 comment in 2 years 5 months
approximate-nearest-neighbor-searchsimilarity-searchvectorvector-databaseai-applications
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