About Zilliz Zilliz is building the next generation of data infrastructure for AI. Founded in 2017 by the creators of Milvus, one of the world's most popular open-source vector databases, we help developers and enterprises build, deploy, and scale AI-powered applications, from semantic search and RAG to emerging agentic AI workloads.

Backed by $113 million in funding from leading global investors, Zilliz has established a strong presence in the AI infrastructure market. Milvus has earned over 46,000 GitHub stars, and our technology has reached more than 10,000 enterprise users worldwide. Companies including OpenEvidence, Exa, and Filevine rely on Zilliz Cloud to power their AI applications.

Building on our roots in vector database technology, we're expanding Zilliz Cloud into a broader AI data platform with Zilliz Vector Lakebase. As AI continues to reshape how applications are built and how data is used, we're focused on making the underlying infrastructure more powerful, scalable, and accessible to organizations worldwide.

The Vector Index team focuses on building the core vector retrieval capabilities behind Milvus, Zilliz Cloud, and Vector Lakebase. We work on making similarity search over massive embedding datasets faster, more accurate, and more cost-efficient, while continuously advancing ANN algorithms, index structures, quantization, compression, recall optimization, CPU/GPU acceleration, and high-performance retrieval frameworks. This role sits at the intersection of research and engineering. You will read papers, evaluate new algorithms, build prototypes, and turn promising ideas into production-grade vector indexing and retrieval systems. We are looking for engineers who enjoy research, but also have strong engineering fundamentals, performance optimization skills, and engineering taste.