{"schemaVersion":"jobsearcher.job.v1","id":"9d05161b8f1567e49b93e9ef","url":"https://jobsearcher.com/jobs/9d05161b8f1567e49b93e9ef","canonicalUrl":"https://jobsearcher.com/jobs/9d05161b8f1567e49b93e9ef","title":"ML Ops Engineer","description":"ML Ops Engineer\nBay Area, CA\nHybrid Position\nResponsibilities\nDesign the data pipelines and engineering infrastructure to support our clients’ enterprise machine learning systems at scale\nTake offline models data scientists build and turn them into a real machine learning production system\nDevelop and deploy scalable tools and services for our clients to handle machine learning training and inference\nIdentify and evaluate new technologies to improve performance, maintainability, and reliability of our clients’ machine learning systems\nApply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.\nSupport model development, with an emphasis on auditability, versioning, and data security\nFacilitate the development and deployment of proof-of-concept machine learning systems\nCommunicate with clients to build requirements and track progress\nQualifications\nExperience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)\nStrong software engineering skills in complex, multi-language systems\nFluency in Python\nComfort with Linux administration\nExperience working with cloud computing and database systems\nExperience building custom integrations between cloud-based systems using APIs\nExperience developing and maintaining ML systems built with open source tools\nExperience developing with containers and Kubernetes in cloud computing environments\nFamiliarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)\nAbility to translate business needs to technical requirements\nStrong understanding of software testing, benchmarking, and continuous integration\nExposure to machine learning methodology and best practices\nExposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)\nJob Type: Full-time\nPay: $60.00 - $62.00 per hour\nSchedule:\n8 hour shift\nWork Location: In person","company":"Systems","rawCompany":"systems","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-10T13:19:00.089Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"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":"ML Ops Engineer","description":"ML Ops Engineer\nBay Area, CA\nHybrid Position\nResponsibilities\nDesign the data pipelines and engineering infrastructure to support our clients’ enterprise machine learning systems at scale\nTake offline models data scientists build and turn them into a real machine learning production system\nDevelop and deploy scalable tools and services for our clients to handle machine learning training and inference\nIdentify and evaluate new technologies to improve performance, maintainability, and reliability of our clients’ machine learning systems\nApply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.\nSupport model development, with an emphasis on auditability, versioning, and data security\nFacilitate the development and deployment of proof-of-concept machine learning systems\nCommunicate with clients to build requirements and track progress\nQualifications\nExperience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent)\nStrong software engineering skills in complex, multi-language systems\nFluency in Python\nComfort with Linux administration\nExperience working with cloud computing and database systems\nExperience building custom integrations between cloud-based systems using APIs\nExperience developing and maintaining ML systems built with open source tools\nExperience developing with containers and Kubernetes in cloud computing environments\nFamiliarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)\nAbility to translate business needs to technical requirements\nStrong understanding of software testing, benchmarking, and continuous integration\nExposure to machine learning methodology and best practices\nExposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)\nJob Type: Full-time\nPay: $60.00 - $62.00 per hour\nSchedule:\n8 hour shift\nWork Location: In person","datePosted":"2026-08-10T13:19:00.089Z","dateModified":"2026-08-10T13:19:00.089Z","hiringOrganization":{"@type":"Organization","name":"Systems","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"9d05161b8f1567e49b93e9ef"},"url":"https://jobsearcher.com/jobs/9d05161b8f1567e49b93e9ef"}}