Senior Software Engineer - Search

<p>P-926</p> <p>The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks.&nbsp;</p> <p>As our Search product continues to evolve, we are seeking multiple <strong>&nbsp;ML Engineers from junior levels to more senior levels</strong> to drive enhancements to our Search Quality. In 2026, we will focus on enhancing <strong>search ranking, improving query understanding, building robust evals</strong> and growing the coverage of assets to enable seamless search at scale.</p> <p><strong>Key Responsibilities</strong></p> <ul> <li>Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services.&nbsp;</li> <li>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.&nbsp;</li> <li>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.&nbsp;</li> <li>Contribute to building a robust framework for evaluating search ranking improvements - both offline and online.</li> </ul> <p>&nbsp;</p> <p><strong>What We’re Looking For</strong></p> <ul> <li>BS+ (M.S. or PhD preferred) in Computer Science, or a related field.</li> <li>5+ years experience <strong>developing search relevance systems at scale</strong> in production or in high-impact research environments.</li> <li>Experience applying LLM to search relevance</li> <li>Experience in one or more of the following:&nbsp;&nbsp;</li> <ul> <li>Query understanding</li> <li>NLP</