Senior Vector Search Engineer for Scalable AI Retrieval

ByteDance; San Jose (CA); On-site; USD 218,000 - 480,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) with company match

Paid parental leave

Wellbeing benefits

Paid holidays and sick days

Job summary

ByteDance is seeking engineers to advance our search and vector database capabilities, including integration with Elasticsearch/OpenSearch and Milvus. You will work on high-performance full-text and vector search, hybrid search, and large-scale ANN retrieval across distributed systems.

The role emphasizes cloud-native architectures and scalable retrieval, with exposure to modern AI-powered search workloads and data lake storage considerations.

Qualifications

• B.S in Computer Science, AI, Machine Learning, or a related field.
• Strong software engineering skills in C++, Golang, Java, or Python.
• Experience with search engines, databases, storage systems, or distributed systems.
• Hands‑on experience with Elasticsearch/OpenSearch or Milvus in production or system development.
• Strong understanding of distributed systems and performance optimization.

Responsibilities

• Develop and evolve our Elasticsearch/OpenSearch and Milvus products, building high-performance and scalable search and vector retrieval capabilities.
• Develop high-performance full-text and vector search, including hybrid search, filtered search, multi-vector search, and large-scale ANN retrieval.
• Optimize vector indexing and distributed retrieval across HNSW, IVF, DiskANN, RaBitQ, storage, caching, and I/O.
• Explore cloud-native Vector Lakebase architectures for scalable search over data lakes and object storage.

Skills

C++

Golang

Java

Python

Education

B.S in Computer Science, AI, Machine Learning, or a related field

Tools

Elasticsearch/OpenSearch

Milvus

Job description

ByteDance is seeking engineers to advance our search and vector database capabilities, including integration with Elasticsearch/OpenSearch and Milvus. You will work on high-performance full-text and vector search, hybrid search, and large-scale ANN retrieval across distributed systems.

The role emphasizes cloud-native architectures and scalable retrieval, with exposure to modern AI-powered search workloads and data lake storage considerations.