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YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_deb98db6-eba"},"title":"Staff Software Engineer, Search Quality","description":"<p>At Databricks, we are enabling data teams to solve the world&#39;s toughest problems by building and running the world&#39;s best data and AI infrastructure platform.来たSearch plays a foundational role in this mission, powering everything from Retrieval Augmented Generation (RAG), AI assistants, and recommendation systems to enterprise knowledge management, in-product search, and data exploration.</p>\n<p>As a Staff Software Engineer for Search Quality, you will drive the technical direction of ranking, relevance, evaluation, and quality initiatives across Databricks&#39; next-generation Search product. You&#39;ll design and build the systems, models, and evaluation frameworks that ensure our Search stack delivers accurate, high-quality results across diverse multimodal datasets and query patterns.</p>\n<p>The impact you will have:</p>\n<ul>\n<li>Lead the technical vision for Search Quality, shaping the ranking architecture, relevance modeling stack, and evaluation systems that power Databricks&#39; next-generation retrieval experiences.</li>\n</ul>\n<ul>\n<li>Identify and solve challenges in ranking, query understanding, and hybrid retrieval , advancing state-of-the-art techniques in vector, keyword, and multimodal search.</li>\n</ul>\n<ul>\n<li>Design and train production-ready ranking and reranking models with strong guarantees around quality, latency, and resource efficiency.</li>\n</ul>\n<ul>\n<li>Partner closely with research, product, and infra teams to define metrics, evaluation methodologies, and experimentation strategies for new retrieval features and model architectures.</li>\n</ul>\n<ul>\n<li>Drive end-to-end engineering efforts , from early prototyping to production rollout , ensuring correctness, reliability, and measurable improvements to relevance.</li>\n</ul>\n<ul>\n<li>Build and operate resilient, low-latency services for ranking, evaluation, and relevance signal processing.</li>\n</ul>\n<ul>\n<li>Champion excellence in ML and search engineering, mentoring teammates and elevating design, code quality, and scientific rigor across the team.</li>\n</ul>\n<ul>\n<li>Shape Databricks&#39; long-term roadmap for retrieval quality, ranking infrastructure, and the foundations for retrieval-driven AI products.</li>\n</ul>\n<p>What we look for:</p>\n<ul>\n<li>10+ years of experience building large-scale search, ranking, recommendation, or ML-driven relevance systems.</li>\n</ul>\n<ul>\n<li>Deep expertise in Search Quality, including ranking models, signals, query understanding, and evaluation methodologies.</li>\n</ul>\n<ul>\n<li>Strong understanding of relevance metrics and evaluation frameworks.</li>\n</ul>\n<ul>\n<li>Familiarity with vector search, keyword search, hybrid retrieval, and embedding-based semantic retrieval.</li>\n</ul>\n<ul>\n<li>Solid foundation in algorithms, data structures, and system design for performance-critical ranking and retrieval systems.</li>\n</ul>\n<ul>\n<li>Proven ability to deliver high-impact technical initiatives with clear business or product outcomes.</li>\n</ul>\n<ul>\n<li>Strong communication skills and ability to collaborate across teams in fast-moving environments.</li>\n</ul>\n<ul>\n<li>Strategic and product-oriented mindset with the ability to align technical execution with long-term vision.</li>\n</ul>\n<ul>\n<li>Passion for mentoring, growing engineers, and fostering technical excellence.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_deb98db6-eba","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Databricks","sameAs":"https://databricks.com","logo":"https://logos.yubhub.co/databricks.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/databricks/jobs/8295792002","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$165,300-$219,675 USD","x-skills-required":["large-scale search","ranking","recommendation","ML-driven relevance systems","Search Quality","ranking models","signals","query understanding","evaluation methodologies","relevance metrics","evaluation frameworks","vector search","keyword search","hybrid retrieval","embedding-based semantic retrieval","algorithms","data structures","system design"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:44:36.338Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, California"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"large-scale search, ranking, recommendation, ML-driven relevance systems, Search Quality, ranking models, signals, query understanding, evaluation methodologies, relevance metrics, evaluation frameworks, vector search, keyword search, hybrid retrieval, embedding-based semantic retrieval, algorithms, data structures, system design","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":165300,"maxValue":219675,"unitText":"YEAR"}}}]}