{"schemaVersion":"jobsearcher.job.v1","id":"936f4bd191bf0836c8efc647","url":"https://jobsearcher.com/jobs/936f4bd191bf0836c8efc647","canonicalUrl":"https://jobsearcher.com/jobs/936f4bd191bf0836c8efc647","title":"Senior Applied ML Engineer - ML4Sys","description":"RDQ127R59\n\nSummary\nAs a Senior Applied ML Engineer on the Applied AI team at Databricks, you will use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure. Your work will span the entire stack—from cluster management down to query compilation. You will solve complex, high-impact engineering problems to deliver highly optimized, cost-effective workloads for our customers.\nImpact You Will Have\nAccelerate Serverless Growth: Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques.\nBuild Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support\nShape Strategy: Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks.\nDrive Deployment: Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency.\nScale Infrastructure: Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems to help scale\nInnovate: Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments.\nMinimum Qualifications\nEducation: Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc).\nML Experience: Strong background in building, training, and deploying machine learning models in production.\nInfrastructure Knowledge: Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks.\nCore Coding: Proficiency in Python, Scala, or Java.\nPreferred Skills\nAdvanced Education: PhD in AI, Data Science, or a related technical discipline.\nIndustry Experience: 4+ years of machine learning engineering experience in high-velocity, high-growth environment.\nSystems Domain: Strong understanding of computer architecture, distributed computing, cloud compute, database internals, or networking.\nOptimization: Experience with operations research, forecasting, markov decision processes, or other optimization algorithms for sequential decision making.\nScale: Proven track record of optimizing large-scale distributed systems or cloud infrastructure via data-driven approaches.\n\nPay Range Transparency\nDatabricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.\n\nLocal Pay Range\n$16,000—$21,000 USD\nAbout Databricks\nDatabricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.\n\nBenefits\n\nAt Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.\n\nOur Commitment to Diversity and Inclusion\nAt Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.\nCompliance\nIf access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.","company":"Databricks","rawCompany":"databricks","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-04T10:39:14.460Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior Applied ML Engineer - ML4Sys","description":"RDQ127R59\n\nSummary\nAs a Senior Applied ML Engineer on the Applied AI team at Databricks, you will use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure. Your work will span the entire stack—from cluster management down to query compilation. You will solve complex, high-impact engineering problems to deliver highly optimized, cost-effective workloads for our customers.\nImpact You Will Have\nAccelerate Serverless Growth: Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques.\nBuild Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support\nShape Strategy: Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks.\nDrive Deployment: Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency.\nScale Infrastructure: Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems to help scale\nInnovate: Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments.\nMinimum Qualifications\nEducation: Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc).\nML Experience: Strong background in building, training, and deploying machine learning models in production.\nInfrastructure Knowledge: Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks.\nCore Coding: Proficiency in Python, Scala, or Java.\nPreferred Skills\nAdvanced Education: PhD in AI, Data Science, or a related technical discipline.\nIndustry Experience: 4+ years of machine learning engineering experience in high-velocity, high-growth environment.\nSystems Domain: Strong understanding of computer architecture, distributed computing, cloud compute, database internals, or networking.\nOptimization: Experience with operations research, forecasting, markov decision processes, or other optimization algorithms for sequential decision making.\nScale: Proven track record of optimizing large-scale distributed systems or cloud infrastructure via data-driven approaches.\n\nPay Range Transparency\nDatabricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.\n\nLocal Pay Range\n$16,000—$21,000 USD\nAbout Databricks\nDatabricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.\n\nBenefits\n\nAt Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.\n\nOur Commitment to Diversity and Inclusion\nAt Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.\nCompliance\nIf access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.","datePosted":"2026-08-04T10:39:14.460Z","dateModified":"2026-08-04T10:39:14.460Z","hiringOrganization":{"@type":"Organization","name":"Databricks","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"936f4bd191bf0836c8efc647"},"url":"https://jobsearcher.com/jobs/936f4bd191bf0836c8efc647"}}