{"schemaVersion":"jobsearcher.job.v1","id":"f0dd41e360075bb09ac6501d","url":"https://jobsearcher.com/jobs/f0dd41e360075bb09ac6501d","canonicalUrl":"https://jobsearcher.com/jobs/f0dd41e360075bb09ac6501d","title":"Staff Engineer, Applied AI","description":"About the Role\nThe Applied AI team at Databricks is 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, some of which can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers, helping them accomplish their tasks.\n\nAs our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2025, we will focus on enhancing search ranking, improving query understanding, building robust evals, and growing the coverage of assets to enable seamless search at scale.\n\nKey Responsibilities\n\nDrive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services.\n\nDesign 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.\n\nCollaborate 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.\n\nContribute to building a robust framework for evaluating search ranking improvements - both offline and online.\n\nWhat We’re Looking For\n\nBS+ (M.S. or PhD preferred) in Computer Science, or a related field.\n\n10+ years experience developing search relevance systems at scale in production or in high-impact research environments.\n\nExperience applying LLM to search relevance.\n\nExperience in one or more of the following:\n\nQuery understanding\n\nNLP\n\nText mining\n\nRecommendations\n\nPersonalization\n\nDiscovery\n\nConversational AI\n\nStrong understanding of computer science fundamentals.\n\nContributions to well-used open-source projects.\n\n#J-18808-Ljbffr","company":"Gravity Engineering Services","rawCompany":"gravity engineering services","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-07-16T04:03:29.410Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Staff Engineer, Applied AI","description":"About the Role\nThe Applied AI team at Databricks is 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, some of which can have hundreds of millions of assets. Finding an asset is a critical user journey for Databricks’ customers, helping them accomplish their tasks.\n\nAs our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. In 2025, we will focus on enhancing search ranking, improving query understanding, building robust evals, and growing the coverage of assets to enable seamless search at scale.\n\nKey Responsibilities\n\nDrive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services.\n\nDesign 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.\n\nCollaborate 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.\n\nContribute to building a robust framework for evaluating search ranking improvements - both offline and online.\n\nWhat We’re Looking For\n\nBS+ (M.S. or PhD preferred) in Computer Science, or a related field.\n\n10+ years experience developing search relevance systems at scale in production or in high-impact research environments.\n\nExperience applying LLM to search relevance.\n\nExperience in one or more of the following:\n\nQuery understanding\n\nNLP\n\nText mining\n\nRecommendations\n\nPersonalization\n\nDiscovery\n\nConversational AI\n\nStrong understanding of computer science fundamentals.\n\nContributions to well-used open-source projects.\n\n#J-18808-Ljbffr","datePosted":"2026-07-16T04:03:29.410Z","dateModified":"2026-07-16T04:03:29.410Z","hiringOrganization":{"@type":"Organization","name":"Gravity Engineering Services","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"f0dd41e360075bb09ac6501d"},"url":"https://jobsearcher.com/jobs/f0dd41e360075bb09ac6501d"}}