{"schemaVersion":"jobsearcher.job.v1","id":"3372e6bc37e91c2f92ea2b49","url":"https://jobsearcher.com/jobs/3372e6bc37e91c2f92ea2b49","canonicalUrl":"https://jobsearcher.com/jobs/3372e6bc37e91c2f92ea2b49","title":"Research Engineer, Bellwether, X","description":"About the Team\r\nOur team - Bellwether - operates at the intersection of machine learning, geospatial data, and pressing issues with enterprise customers, governments, and more. We focus on severe weather manifestations of climate change, such as wildfires, and aim to use a wide range of data and analytics to better understand and predict what these events could mean for communities and businesses across the globe. We do this through the detection and classification of the features and patterns of the natural and built worlds, the application of cutting-edge machine learning, and the redesign of the full geo-ML workflow. This work extends into development and production-level work as well, as Bellwether also has a number of products that are live with customers. The result: tools and models that allow a range of industries to better leverage earth observation insights.\r\nAbout the role\r\nYou will be a hands-on Machine Learning engineer, contributing to all aspects of the project's development and deployment of applications. This role would guide machine learning for Bellwether's real-world products, and is not a research-based role.\r\nOur team is small but mighty and highly collaborative, and values pair programming and cooperative ideation. We are committed to agile principles and rely heavily on this framework for efficient sprints and cycles. We are looking for passionate and driven people, who are comfortable moving between creative, big-picture thinking and specifics of how to execute. We operate in a fast-paced, fluid environment as our team moves from early stage development into production phases.\r\nHow you will make 10x impact\r\n\r\nContribute as a key team member to the creation of new systems and processes to ensure high quality development, deployment, and maintenance of live applications in production environments\r\nCreate and maintain Google Cloud Platform-based infrastructure for software development and high-volume production systems.\r\nCollaborate with team members, internal and external stakeholders, and help execute on the direction for future development.\r\n\r\nWhat you should have\r\n\r\nPhD in Computer Science or equivalent practical experience\r\n7 years experience with the machine learning development pipeline: research, experimentation, and ML-Ops\r\nExpertise in ML frameworks (e.g., PyTorch, TensorFlow/Keras/JAX) and Python libraries (e.g., NumPy, SciPy, Pandas).\r\nExperience with numerous common software design patterns (for example, Observer, Decorator, Visitor, Producer/Consumer, etc).\r\nExperience with open source tools such as: Git, TensorFlow, Apache Beam/Dataflow, Google Compute Engine.\r\nPython proficiency.\r\nExperience working on an early stage project and environment where prototype technologies are evolved into a production phase.\r\nAn ability to thrive in an Agile-driven team: iteratively sprinting toward goals and products, contributing new ideas, standards, and processes.\r\nExperience interfacing with customers\r\n\r\nIt'd be great if you also had these:\r\n\r\nProduction-level experience in the geospatial industry, with a wide variety of tasks, including code development, designing for, implementing, and managing security measures and controls, troubleshooting and debugging, designing and implementing code testing processes, and monitoring deployed application's performance and health.\r\nExperience working  with a wide variety of geospatial data\r\nExperience in Machine Learning Operations - scaling existing machine learning applications into production\r\n\r\nThe US base salary range for this full-time position is $174,000 - $255,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.\r\nPlease note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.","company":"X","rawCompany":"x","city":"Mountain View","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-06-11T15:14:30.569Z","occupations":[{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541715","title":"Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)","slug":"research-and-development-in-the-physical-engineering-and-life-sciences-except-nanotechnology-and-biotechnology"},{"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":"Research Engineer, Bellwether, X","description":"About the Team\r\nOur team - Bellwether - operates at the intersection of machine learning, geospatial data, and pressing issues with enterprise customers, governments, and more. We focus on severe weather manifestations of climate change, such as wildfires, and aim to use a wide range of data and analytics to better understand and predict what these events could mean for communities and businesses across the globe. We do this through the detection and classification of the features and patterns of the natural and built worlds, the application of cutting-edge machine learning, and the redesign of the full geo-ML workflow. This work extends into development and production-level work as well, as Bellwether also has a number of products that are live with customers. The result: tools and models that allow a range of industries to better leverage earth observation insights.\r\nAbout the role\r\nYou will be a hands-on Machine Learning engineer, contributing to all aspects of the project's development and deployment of applications. This role would guide machine learning for Bellwether's real-world products, and is not a research-based role.\r\nOur team is small but mighty and highly collaborative, and values pair programming and cooperative ideation. We are committed to agile principles and rely heavily on this framework for efficient sprints and cycles. We are looking for passionate and driven people, who are comfortable moving between creative, big-picture thinking and specifics of how to execute. We operate in a fast-paced, fluid environment as our team moves from early stage development into production phases.\r\nHow you will make 10x impact\r\n\r\nContribute as a key team member to the creation of new systems and processes to ensure high quality development, deployment, and maintenance of live applications in production environments\r\nCreate and maintain Google Cloud Platform-based infrastructure for software development and high-volume production systems.\r\nCollaborate with team members, internal and external stakeholders, and help execute on the direction for future development.\r\n\r\nWhat you should have\r\n\r\nPhD in Computer Science or equivalent practical experience\r\n7 years experience with the machine learning development pipeline: research, experimentation, and ML-Ops\r\nExpertise in ML frameworks (e.g., PyTorch, TensorFlow/Keras/JAX) and Python libraries (e.g., NumPy, SciPy, Pandas).\r\nExperience with numerous common software design patterns (for example, Observer, Decorator, Visitor, Producer/Consumer, etc).\r\nExperience with open source tools such as: Git, TensorFlow, Apache Beam/Dataflow, Google Compute Engine.\r\nPython proficiency.\r\nExperience working on an early stage project and environment where prototype technologies are evolved into a production phase.\r\nAn ability to thrive in an Agile-driven team: iteratively sprinting toward goals and products, contributing new ideas, standards, and processes.\r\nExperience interfacing with customers\r\n\r\nIt'd be great if you also had these:\r\n\r\nProduction-level experience in the geospatial industry, with a wide variety of tasks, including code development, designing for, implementing, and managing security measures and controls, troubleshooting and debugging, designing and implementing code testing processes, and monitoring deployed application's performance and health.\r\nExperience working  with a wide variety of geospatial data\r\nExperience in Machine Learning Operations - scaling existing machine learning applications into production\r\n\r\nThe US base salary range for this full-time position is $174,000 - $255,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.\r\nPlease note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.","datePosted":"2026-06-11T15:14:30.569Z","dateModified":"2026-06-11T15:14:30.569Z","hiringOrganization":{"@type":"Organization","name":"X","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"3372e6bc37e91c2f92ea2b49"},"url":"https://jobsearcher.com/jobs/3372e6bc37e91c2f92ea2b49"}}