Senior Research Scientist – Infrastructure System Lab
| Company | ByteDance |
|---|---|
| Location | Seattle, WA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | PhD |
| Experience Level | Senior |
Requirements
- PhD in Computer Science, Applied Mathematics, Electrical Engineering, or a related technical field.
- Strong publication record in top-tier venues (e.g., SIGMOD, VLDB, SIGIR, NeurIPS, ICML, etc.) related to vector search, indexing, IR, or ML.
- Deep understanding of ANN algorithms, quantization, graph-based indexes, and partition-based indexes.
- Strong system-level thinking: ability to profile, benchmark, and optimize performance across CPU, memory, and storage layers.
- Proficiency in C++ and/or Python, with experience in implementing and benchmarking algorithms.
Responsibilities
- Research and develop new algorithms for approximate nearest neighbor (ANN) search, especially for filtered, hybrid, or disk-based scenarios.
- Optimize existing algorithms for scalability, low latency, memory footprint, and hybrid search support.
- Collaborate with engineering teams to prototype, benchmark, and productionize indexing solutions.
- Contribute to academic publications, open-source libraries, or internal technical documentation.
- Stay current with research trends in vector search, retrieval systems, retrieval-augmented generation (RAG), large language models (LLMs), and related areas.
Preferred Qualifications
- Experience building or contributing to vector databases or retrieval engines in production.
- Familiarity with frameworks like FAISS, ScaNN, HNSWLib, or DiskANN.
- Understanding of distributed systems and/or GPU-accelerated search.
- Experience with hybrid search (dense + sparse), multi-modal retrieval, or retrieval for LLMs.
- Passion for bridging theory and practice in production-scale systems.