Senior Software Engineer, Vector Index Research
On-siteRedwood City, California, United States
Job Summary
Senior Software Engineer, Vector Index Research responsible for researching, evaluating, and implementing 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.
Required Qualifications
- 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
- 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 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
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