Zilliz

Full-stack Engineer

• 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

Senior Software Engineer, Vector Index Research

• Design and build the cloud platform behind Zilliz Cloud and Vector Lakebase, bringing together cloud control plane, database runtime, scheduling, resource management, deployment, and lifecycle management to support fast workload placement, elastic scaling, multi-tenant isolation, and cost-efficient execution
• Build cloud-native systems that make distributed database provisioning, scaling, upgrades, recovery, and workload migration automated, observable, rollback-safe, and efficient
• Work deep across Kubernetes, multi-cloud infrastructure, networking, storage, and database engine runtimes to deliver a tightly integrated cloud-and-engine product experience
• Improve platform scalability, reliability, performance, and operational simplicity as we grow across customers, regions, tenants, datasets, and AI workloads
• Partner with database, reliability, and product engineers to bring new Vector Lakebase capabilities into cloud production safely and quickly
• Use AI deeply across the platform engineering workflow, including deployment validation, diagnosis, incident analysis, capacity planning, documentation, code generation, and operational tooling

Senior Software Engineer, Vector Index Research

Senior Software Engineer, Cloud Platform