{"schemaVersion":"jobsearcher.job.v1","id":"3703bc97f8b116a5e72f6f7a","url":"https://jobsearcher.com/jobs/3703bc97f8b116a5e72f6f7a","canonicalUrl":"https://jobsearcher.com/jobs/3703bc97f8b116a5e72f6f7a","title":"Machine Learning Staff Software Engineer, Pixel Camera","description":"Overview\nIn this role you will design and implement a real-time ML foundation that turns raw camera and sensor data into actionable signals on-device. You will optimize models for NPU, GPU, and DSP, collaborating with Tensor silicon and compiler teams to craft hardware-aware architectures and custom kernels. You own end-to-end model life cycles—from research prototypes to production on hundreds of millions of devices—leveraging JAX and TensorFlow pipelines and integrating C++ into the camera stack. You’ll partner across product, UX, software, and hardware teams to translate roadmaps into feasible device-level designs, set best practices, and shape the long-term ML roadmap.\n\nCompensation / Benefitsbonus target (20%)equitybenefitscompetitive compensation (US: 207000-300000)\nResponsibilitiesDesign and implement real-time on-device ML foundation for signal extraction from camera/sensor inputOptimize models for on-device accelerators (NPU, GPU, DSP) including quantization and hardware-aware architecture designDevelop and maintain end-to-end model lifecycle from prototype to production on mobile/embedded devicesBuild training pipelines using JAX and TensorFlow; integrate C++ into the camera pipelineCollaborate with product, UX, software, and hardware teams to translate roadmaps into device-constrained designsEstablish best practices for ML development, deployment, and evaluation; define model quality metrics and contribute to the technology roadmap\nKey requirementsBachelor's degree in any field or equivalent practical experience8 years of experience in software design and architectureExperience with C, C++, machine learning, and embedded systemsExperience with machine learning algorithms, architectures, and researchCollaboration across cross-functional teamsLeadership and initiativeAdaptability and problem-solving in fast-paced environmentsC, C++Machine learning algorithms and architecturesEmbedded systems experience","company":"Google","rawCompany":"google","city":"San Jose","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-09-22T03:15:20.777Z","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":"17-2061.00","title":"Computer Hardware Engineers","slug":"computer-hardware-engineers"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Staff Software Engineer, Pixel Camera","description":"Overview\nIn this role you will design and implement a real-time ML foundation that turns raw camera and sensor data into actionable signals on-device. You will optimize models for NPU, GPU, and DSP, collaborating with Tensor silicon and compiler teams to craft hardware-aware architectures and custom kernels. You own end-to-end model life cycles—from research prototypes to production on hundreds of millions of devices—leveraging JAX and TensorFlow pipelines and integrating C++ into the camera stack. You’ll partner across product, UX, software, and hardware teams to translate roadmaps into feasible device-level designs, set best practices, and shape the long-term ML roadmap.\n\nCompensation / Benefitsbonus target (20%)equitybenefitscompetitive compensation (US: 207000-300000)\nResponsibilitiesDesign and implement real-time on-device ML foundation for signal extraction from camera/sensor inputOptimize models for on-device accelerators (NPU, GPU, DSP) including quantization and hardware-aware architecture designDevelop and maintain end-to-end model lifecycle from prototype to production on mobile/embedded devicesBuild training pipelines using JAX and TensorFlow; integrate C++ into the camera pipelineCollaborate with product, UX, software, and hardware teams to translate roadmaps into device-constrained designsEstablish best practices for ML development, deployment, and evaluation; define model quality metrics and contribute to the technology roadmap\nKey requirementsBachelor's degree in any field or equivalent practical experience8 years of experience in software design and architectureExperience with C, C++, machine learning, and embedded systemsExperience with machine learning algorithms, architectures, and researchCollaboration across cross-functional teamsLeadership and initiativeAdaptability and problem-solving in fast-paced environmentsC, C++Machine learning algorithms and architecturesEmbedded systems experience","datePosted":"2026-09-22T03:15:20.777Z","dateModified":"2026-09-22T03:15:20.777Z","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":"3703bc97f8b116a5e72f6f7a"},"url":"https://jobsearcher.com/jobs/3703bc97f8b116a5e72f6f7a"}}