About the company
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog.
Responsibilities
- Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services.
- Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration.
- Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience.
- Contribute to building a robust framework for evaluating search ranking improvements - both offline and online.
Requirements
- BS+ (M.S. or PhD preferred) in Computer Science, or a related field.
- 5+ years experience developing search relevance systems at scale in production or in high-impact research environments.
- Experience applying LLM to search relevance.
- Experience in one or more of the following: Query understanding, NLP, Text mining, Recommendations, Personalization, Discovery, Conversational AI.
- Strong understanding of computer science fundamentals.
- Contributions to well-used open-source projects.