---
title: 'Senior Software Engineer, Vector Index Research at Zilliz'
canonical: 'https://feeny.ai/job/senior-software-engineer-vector-index-research-zilliz-redwood-city-4v3hvtr0jp3f'
type: 'job'
last_seen: '2026-09-11'
---

# Senior Software Engineer, Vector Index Research at Zilliz

- **Company:** Zilliz
- **Location:** Redwood City, CA
- **Compensation:** $175k–$250k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-06-22
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.lever.co/zilliz/5e73c85a-7acf-43f1-8936-68396bb74e82

## Job description

Zilliz is a fast-growing startup developing the industry’s leading vector database for enterprise-grade AI. Founded by the engineers behind Milvus, the world’s most popular open-source vector database, the company builds next-generation database technologies to help organizations quickly create AI applications. On a mission to democratize AI, Zilliz is committed to simplifying data management for AI applications and making vector databases accessible to every organization.

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.

What you'll do:

- Research, evaluate, and implement new vector indexing and retrieval algorithms for Milvus, Zilliz Cloud, and Vector Lakebase
- Read papers and track emerging work in vector search, ANN algorithms, index structures, quantization, compression, reranking, GPU acceleration, and AI retrieval systems
- Build high-performance vector indexing components, including index building, query paths, vector preprocessing, quantization, compression, memory layout, and CPU/GPU acceleration
- Optimize vector retrieval performance across latency, throughput, recall, memory usage, index build time, and cost efficiency
- Design benchmarks and evaluation frameworks to compare algorithms and implementations under real data scale, real query patterns, and real AI workloads
- Debug and solve complex performance issues across algorithm implementation, CPU/GPU execution, SIMD/vectorization, memory access, concurrency, and I/O
- Turn research prototypes into maintainable, testable, and evolvable production-grade indexing capabilities
- Use AI tools across the research and engineering workflow, including paper analysis, prototype generation, code implementation, testing, benchmarking, documentation, and performance analysis

What we're looking for:

- 3+ years of experience in vector search, ANN algorithms, search systems, high-performance computing, or performance-critical systems
- Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience
- Strong C++ or Rust programming ability and solid engineering fundamentals
- Experience with vector similarity search, ANN algorithms, index structures, quantization, compression, reranking, or high-performance retrieval systems is a strong plus
- Strong interest in research-driven engineering: reading papers, evaluating tradeoffs, building prototypes, and turning ideas into production systems
- Experience with performance optimization and systematic debugging is a strong plus, especially around CPU/GPU execution, SIMD, memory layout, concurrency, I/O, or large-scale data processing
- Interest in using AI tools to improve research, coding, testing, benchmarking, documentation, and performance analysis

How we operate:

- Research-driven, production-focused: We track frontier algorithms, but care most about whether they work under real data scale, real query patterns, and real production constraints
- Extreme performance: We care about every memory access, every query path, and every tradeoff between recall and latency
- AI-first engineering: We actively use AI to accelerate paper reading, prototyping, coding, testing, documentation, and performance analysis, but human judgment and engineering taste still matter most
- Fast and pragmatic: We work on hard vector indexing and retrieval problems, but we ship them into Milvus, Zilliz Cloud, and Vector Lakebase
- Open source by default: Milvus is a core part of our engineering culture, and strong indexing capabilities should stand up to public design, code, and community usage

Benefits:

- Competitive compensation (cash + equity)
- Regular bonus and equity refresh opportunities
- Medical, dental, and vision insurance
- Paid time off, including vacation, sick leave, and global reset/wellbeing days
- Generous 401(k) and regional retirement plans

Zilliz is an Equal Opportunity Employer and welcomes people from all backgrounds, experiences, abilities, and perspectives. All qualified applicants will receive consideration for employment regardless of race, color, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, or length of time spent unemployed.

## About Zilliz

## Company Overview
- **One-liner**: Zilliz builds the world’s most popular open-source vector database, Milvus, and offers a fully managed Vector Lakebase to power enterprise AI applications at any scale.
- **Entity Type**: Private (Series B, $113M total funding)
- **Headquarters**: Redwood City, California, United States
- **Founded**: 2017
- **Founders**: Charles Xie (CEO) and James Luan (CTO)

## Core Business
- **Primary industries**: Vector database management, AI infrastructure, software development
- **Target customers**: B2B enterprise (10,000+ enterprise users)
- **Mission**: To make vector database capabilities accessible to every developer and organization, helping them harness unstructured data for AI/ML applications.

## Products & Services
- **[Milvus (Open-Source Vector Database)](https://zilliz.com/about)**: The leading open-source vector database, originally created by Zilliz and hosted under LF AI. Enables billion-scale similarity search, hybrid retrieval (vector, text, JSON, geospatial), and is production-tested across thousands of enterprises.
- **[Zilliz Vector Lakebase](https://zilliz.com/)**: A fully managed cloud service built on Milvus that unifies real-time vector search, lake-scale discovery, and AI data operations. Features include on-demand pay-per-query pricing, hot-cache on S3 for 90% cost reduction, multi-tenancy, and seamless backfill/schema iteration.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total funding of $113 million; annual revenue estimated at $2.2 million (as of latest report)
- **Notable Investors/Partners**: Series A led by 5Y Capital (2018); Series B led by Hillhouse Investment ($43M, 2020); Series B extension led by Prosperity7 Ventures ($60M, 2022)
- **Growth Signals**: 91 employees (8.9% YoY growth); 25,000+ LinkedIn followers (100% yearly growth); 10 active job postings (42.9% increase YoY); offices in Redwood City, New York, Shanghai, London, Berlin, Singapore

## Competitive Advantages
- **Open-source ecosystem**: Milvus is the most widely adopted open-source vector database, with a strong community and 10,000+ enterprise users.
- **Proven at scale**: Production-tested over 8 years, handling 100B+ entities and 10K+ QPS with consistent latency.
- **Cost efficiency**: All data/indexes stored on S3 with hot cache; on-demand compute reduces costs by up to 90%.
- **Full-spectrum search**: Supports hybrid retrieval combining vector, text, JSON, and geospatial queries with filtering and reranking.
- **Vortex format**: An open, next-gen storage format that delivers up to 10x faster random reads than Lance, with per-column flexibility.

## Strategic Focus
- **Enterprise AI adoption**: Expanding the Vector Lakebase to serve massive multi-tenancy, global replication, and low-latency access for AI applications.
- **Global expansion**: Multi-region deployment and offices across the US, Europe, and Asia to support worldwide AI scaling.
- **Continuous innovation**: Investing in research (vector index research roles) and cloud platform reliability to maintain leadership in vector database technology.

## Why Work Here
- **Culture**: Deep technical culture built by the creators of Milvus; engineers and scientists focused on advancing AI and data infrastructure.
- **Work model**: Hybrid/remote opportunities available; offices in Redwood City, New York, Shanghai, London, Berlin, and Singapore.
- **Benefits**: Competitive compensation (cash + equity), regular bonus and equity refresh, comprehensive medical/dental/vision, generous PTO, 401(k) and regional retirement plans, and paid sick leave.
- **Engineering culture**: Work on cutting-edge technology at the intersection of databases and AI, with opportunities to contribute to open source and solve real-world scale challenges.

## Sources
1. [zilliz.com/careers](https://zilliz.com/careers) – Benefits, hybrid work model, company mission
2. [zilliz.com/about](https://zilliz.com/about) – Founding story, leadership, locations, investment, enterprise users
3. [zilliz.com](https://zilliz.com/) – Product details (Vector Lakebase, features, cost savings, scale)
4. [cr.linkedin.com/company/zilliz](https://cr.linkedin.com/company/zilliz) – Employee count, revenue, funding rounds, job postings, demographics
5. [theconsensus.dev/company/zilliz.html](https://theconsensus.dev/company/zilliz.html) – Funding history, job openings

## Other roles at Zilliz

- [Senior Recruiter, GTM](https://feeny.ai/job/senior-recruiter-gtm-zilliz-redwood-city-3dbaw85s6h7t) — Redwood City, CA
- [Senior Recruiter, Technical](https://feeny.ai/job/senior-recruiter-technical-zilliz-redwood-city-r3015tzfhrvh) — Redwood City, CA
- [Senior HR Manager, North America & Europe](https://feeny.ai/job/senior-hr-manager-north-america-europe-zilliz-redwood-city-g3s4fq3wqjat) — Redwood City, CA
- [Senior Software Engineer, Cloud Platform](https://feeny.ai/job/senior-software-engineer-cloud-platform-zilliz-redwood-city-f8sagdsxspja) — Redwood City, CA
- [Enterprise Account Executive - Texas](https://feeny.ai/job/enterprise-account-executive-texas-zilliz-austin-rexebkn8d37m) — Austin, TX
- [Enterprise Account Executive - South Korea](https://feeny.ai/job/enterprise-account-executive-south-korea-zilliz-seoul-d99g77v0qhv9) — Seoul, South Korea
- [Enterprise Account Executive - Japan](https://feeny.ai/job/enterprise-account-executive-japan-zilliz-tokyo-qbdvqknpzq1c) — Tokyo, Japan
- [Enterprise Account Executive - New York](https://feeny.ai/job/enterprise-account-executive-new-york-zilliz-new-york-bcbdq3f8970x) — New York, NY
- [Enterprise Account Executive - Seattle](https://feeny.ai/job/enterprise-account-executive-seattle-zilliz-seattle-2bz0g3gtmzjf) — Seattle, WA
- [Senior Software Engineer, Database Systems](https://feeny.ai/job/senior-software-engineer-database-systems-zilliz-redwood-city-apd7b6eqazwm) — Redwood City, CA