{"schemaVersion":"jobsearcher.job.v1","id":"01edb237b8e93b9089927d08","url":"https://jobsearcher.com/jobs/01edb237b8e93b9089927d08","canonicalUrl":"https://jobsearcher.com/jobs/01edb237b8e93b9089927d08","title":"Software Engineer, On-Device Machine Learning","description":"Overview\nIn this role you will help advance on-device AI by developing and optimizing LiteRT, Google’s on-device AI framework. You will work with cross-functional teams to enable model deployment and acceleration across edge devices and platforms. You will tackle performance, runtime, and kernel improvements to push efficient ML at scale. This is a chance to shape portable AI infrastructure that powers Google products and third-party solutions.\n\nCompensation / Benefits15% bonus targetequitybenefits\nResponsibilitiesCollaborate through design and code reviews to uphold best practices across available technologiesImplement solutions in ML areas and contribute to model optimization and data processingDevelop LiteRT for on-device AI, focusing on hardware acceleration and cross-platform supportEnable on-device deployment of key models (e.g., Gemini Nano, Gemma) across accelerators and platformsImprove on-device runtime and kernel performance to boost inference efficiency\nKey requirementsBachelor’s degree or equivalent practical experience2 years of software development experience or 1 year with advanced degree2 years of ML infrastructure experience (deployment, evaluation, optimization, data processing, debugging)Experience with runtimes and performance tuningExperience in mobile developmentcollaborationleadership qualitiesenthusiasm for solving novel problemsML frameworks: PyTorch, JAX, TensorFlowon-device ML SDKs/tooling: TensorFlow Lite, ExecuTorch, Core ML, SNPE/QNNruntime optimization","company":"Google","rawCompany":"google","city":"San Jose","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-09-15T04:16:24.804Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1299.00","title":"Computer Occupations, All Other","slug":"computer-occupations-all-other"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Software Engineer, On-Device Machine Learning","description":"Overview\nIn this role you will help advance on-device AI by developing and optimizing LiteRT, Google’s on-device AI framework. You will work with cross-functional teams to enable model deployment and acceleration across edge devices and platforms. You will tackle performance, runtime, and kernel improvements to push efficient ML at scale. This is a chance to shape portable AI infrastructure that powers Google products and third-party solutions.\n\nCompensation / Benefits15% bonus targetequitybenefits\nResponsibilitiesCollaborate through design and code reviews to uphold best practices across available technologiesImplement solutions in ML areas and contribute to model optimization and data processingDevelop LiteRT for on-device AI, focusing on hardware acceleration and cross-platform supportEnable on-device deployment of key models (e.g., Gemini Nano, Gemma) across accelerators and platformsImprove on-device runtime and kernel performance to boost inference efficiency\nKey requirementsBachelor’s degree or equivalent practical experience2 years of software development experience or 1 year with advanced degree2 years of ML infrastructure experience (deployment, evaluation, optimization, data processing, debugging)Experience with runtimes and performance tuningExperience in mobile developmentcollaborationleadership qualitiesenthusiasm for solving novel problemsML frameworks: PyTorch, JAX, TensorFlowon-device ML SDKs/tooling: TensorFlow Lite, ExecuTorch, Core ML, SNPE/QNNruntime optimization","datePosted":"2026-09-15T04:16:24.804Z","dateModified":"2026-09-15T04:16:24.804Z","hiringOrganization":{"@type":"Organization","name":"Google","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Jose","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"01edb237b8e93b9089927d08"},"url":"https://jobsearcher.com/jobs/01edb237b8e93b9089927d08"}}