Staff Software Engineer - Machine Learning Search
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 and discovery relevance models integrated into products and services. You will design automated ML and NLP pipelines for preprocessing, query understanding, query rewriting, ranking, retrieval, and model evaluation. You will also build frameworks to evaluate search-ranking improvements offline and online.
Requirements
- 10+ years of experience developing search relevance systems at scale
- Experience applying LLMs to search relevance
- Experience with query understanding, NLP, text mining, recommendations, personalization, discovery, or conversational AI
- Understanding of computer science fundamentals
- Open-source project contributions
Responsibilities
- Develop and deploy ML-based search and discovery relevance models and systems
- Design and implement automated ML and NLP pipelines
- Build pipelines for data preprocessing, query understanding, query rewriting, ranking, retrieval, and model evaluation
- Collaborate on technology initiatives and product roadmaps for search and discovery
- Build frameworks for offline and online evaluation of search-ranking improvements