Staff Software Engineer Search Ranking
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Maintainer signals as of 9/23/2026
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will develop and deploy ML-based search relevance systems. You will build ML and NLP pipelines for query understanding, ranking, retrieval, and evaluation, collaborate on search roadmaps, and create frameworks to measure ranking improvements.
Requirements
- Computer Science
- 10+ years developing production-scale search relevance systems or conducting high-impact search research
- LLM
- Search relevance
- Query understanding
- NLP
- Text mining
- Recommendation
- Personalization
- Discovery
- Conversational AI
- Computer science fundamentals
- Open-source contribution
Responsibilities
- Develop and deploy ML-based search and discovery relevance models
- Design automated ML and NLP pipelines for preprocessing, query understanding, ranking, retrieval, and evaluation
- Collaborate on technology initiatives and search product roadmaps
- Build frameworks for offline and online search-ranking evaluation