{"schemaVersion":"jobsearcher.job.v1","id":"85dba1662ebd283cc5cd2cf5","url":"https://jobsearcher.com/jobs/85dba1662ebd283cc5cd2cf5","canonicalUrl":"https://jobsearcher.com/jobs/85dba1662ebd283cc5cd2cf5","title":"PdM Algorithm Development Engineer","description":"Novity, a spin-out from Xerox’s Palo Alto Research Center (PARC), brings truly predictive maintenance (PdM) technology to the industrial manufacturing sector to reduce costly unplanned downtime. The Novity solution is an Industrial Internet of Things (IIoT) technology that uses IIoT sensors and proprietary algorithms to enable industrial manufacturers to see the future health of their production assets. The Novity TruPrognostics engine relies on a combination of machine learning and physics-based models of equipment. This allows Novity to predict equipment failures with 90 percent or better accuracy and lead times of months, not weeks or days.\nNovity has an immediate opening for a Predictive Maintenance Algorithm Development Engineer with a background in chemical process modeling, or modeling in related process industries, such as oil and gas, food and beverage, wastewater, or similar. The ideal candidate will be passionate about developing solutions for customers that provide a step change in value to their reliability and maintenance programs. Strong candidates will be able to leverage their deep domain expertise and advanced technical skills to develop state of the art diagnostics and prognostics algorithms for industrial IoT applications. The Algorithm Development Engineer will contribute to a modular library of algorithms and models that will be deployed as part of Novity’s predictive maintenance software suite for a wide variety of customers in the process industries. The Algorithm Development Engineer needs to be comfortable with engaging in the end-to-end process of remote monitoring which includes all steps from data collection to analytics results presented back to customer.\nThis position is a remote position with a strong preference for San Francisco Bay Area candidates.\nResponsibilities will include:\nDeveloping physics models of industrial equipment typically found in process industries.\nDeveloping algorithms for online fault detection, diagnostics, and prognostics.\nValidating models and algorithms with a variety of data sources, including simulated data, experimental data and customer data.\nDirecting experimental lab tests, including defining test plans, determining data collection requirements, post-processing data and reporting results.\nDocumenting technical information and communicating it to R&D team members, sales, marketing, management and external stakeholders.\nSupport defining and delivering customer solutions, including instrumentation requirements, algorithm specifications, technical proposals, etc.\nWork in close collaboration with the software and hardware engineering teams, ensuring that algorithms are appropriately deployed in production environment.\nCollaboration with a diverse set of individuals including modeling scientists, data scientists, software and hardware engineers, sales engineers, plant operators, and process industry executives.\nSupporting market research in various process industries and adjacent market verticals.\nRequired experience:\nM.S. or Ph.D. in an engineering field (mechanical or chemical engineering preferred, Ph.D. preferred).\nAt least 3 years of experience in one or more of the following:\nPredictive maintenance or condition monitoring algorithm development for the process industries (oil and gas, chemical, wastewater, etc.).\nChemical process modeling and optimization.\nComputational physics (CFD/FEA/Multiphysics) applied to industrial equipment, such as heat exchangers, separators, reactors, etc.\n\nProgramming experience in Python, Matlab, or similar scientific computing language.\nFamiliarity with production software development tools and concepts, including:CI/CD pipelines\nFunctional and unit tests\nSource control systems\nObject-oriented design\nIntegrated development environments\nDebugging tools\nApplied knowledge of data science methods including exploratory data analysis, statistics, feature extraction, data visualization, etc.\nPreferred experience and skills:\nExperience implementing production machine learning models.\nFamiliarity with industry standards for process control equipment, maintenance, reliability, and monitoring, such as API, ASME, ANSI, ISA, etc.\nFamiliarity with model-based reasoning, particularly model-based prognostics.\nExperience with process or design failure modes and effects analysis (FMEA).\nExperience reading process and instrumentation diagrams, process flow diagrams, and similar.\nIntellectual curiosity, as evidenced by a demonstrated ability and willingness to learn new technologies.\nStrong oral and written communication skills as evidenced by the research output of a graduate-level scholar.\nIf interested, please contact Daniel Nelson at daniel.nelson at novity.us.\n\n#J-18808-Ljbffr","company":"Phm Society","rawCompany":"phm society","city":"San Carlos","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-04-09T09:46:12.509Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"17-2112.00","title":"Industrial Engineers","slug":"industrial-engineers"}],"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":"541330","title":"Engineering Services","slug":"engineering-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"PdM Algorithm Development Engineer","description":"Novity, a spin-out from Xerox’s Palo Alto Research Center (PARC), brings truly predictive maintenance (PdM) technology to the industrial manufacturing sector to reduce costly unplanned downtime. The Novity solution is an Industrial Internet of Things (IIoT) technology that uses IIoT sensors and proprietary algorithms to enable industrial manufacturers to see the future health of their production assets. The Novity TruPrognostics engine relies on a combination of machine learning and physics-based models of equipment. This allows Novity to predict equipment failures with 90 percent or better accuracy and lead times of months, not weeks or days.\nNovity has an immediate opening for a Predictive Maintenance Algorithm Development Engineer with a background in chemical process modeling, or modeling in related process industries, such as oil and gas, food and beverage, wastewater, or similar. The ideal candidate will be passionate about developing solutions for customers that provide a step change in value to their reliability and maintenance programs. Strong candidates will be able to leverage their deep domain expertise and advanced technical skills to develop state of the art diagnostics and prognostics algorithms for industrial IoT applications. The Algorithm Development Engineer will contribute to a modular library of algorithms and models that will be deployed as part of Novity’s predictive maintenance software suite for a wide variety of customers in the process industries. The Algorithm Development Engineer needs to be comfortable with engaging in the end-to-end process of remote monitoring which includes all steps from data collection to analytics results presented back to customer.\nThis position is a remote position with a strong preference for San Francisco Bay Area candidates.\nResponsibilities will include:\nDeveloping physics models of industrial equipment typically found in process industries.\nDeveloping algorithms for online fault detection, diagnostics, and prognostics.\nValidating models and algorithms with a variety of data sources, including simulated data, experimental data and customer data.\nDirecting experimental lab tests, including defining test plans, determining data collection requirements, post-processing data and reporting results.\nDocumenting technical information and communicating it to R&D team members, sales, marketing, management and external stakeholders.\nSupport defining and delivering customer solutions, including instrumentation requirements, algorithm specifications, technical proposals, etc.\nWork in close collaboration with the software and hardware engineering teams, ensuring that algorithms are appropriately deployed in production environment.\nCollaboration with a diverse set of individuals including modeling scientists, data scientists, software and hardware engineers, sales engineers, plant operators, and process industry executives.\nSupporting market research in various process industries and adjacent market verticals.\nRequired experience:\nM.S. or Ph.D. in an engineering field (mechanical or chemical engineering preferred, Ph.D. preferred).\nAt least 3 years of experience in one or more of the following:\nPredictive maintenance or condition monitoring algorithm development for the process industries (oil and gas, chemical, wastewater, etc.).\nChemical process modeling and optimization.\nComputational physics (CFD/FEA/Multiphysics) applied to industrial equipment, such as heat exchangers, separators, reactors, etc.\n\nProgramming experience in Python, Matlab, or similar scientific computing language.\nFamiliarity with production software development tools and concepts, including:CI/CD pipelines\nFunctional and unit tests\nSource control systems\nObject-oriented design\nIntegrated development environments\nDebugging tools\nApplied knowledge of data science methods including exploratory data analysis, statistics, feature extraction, data visualization, etc.\nPreferred experience and skills:\nExperience implementing production machine learning models.\nFamiliarity with industry standards for process control equipment, maintenance, reliability, and monitoring, such as API, ASME, ANSI, ISA, etc.\nFamiliarity with model-based reasoning, particularly model-based prognostics.\nExperience with process or design failure modes and effects analysis (FMEA).\nExperience reading process and instrumentation diagrams, process flow diagrams, and similar.\nIntellectual curiosity, as evidenced by a demonstrated ability and willingness to learn new technologies.\nStrong oral and written communication skills as evidenced by the research output of a graduate-level scholar.\nIf interested, please contact Daniel Nelson at daniel.nelson at novity.us.\n\n#J-18808-Ljbffr","datePosted":"2026-04-09T09:46:12.509Z","dateModified":"2026-04-09T09:46:12.509Z","hiringOrganization":{"@type":"Organization","name":"Phm Society","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Carlos","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"85dba1662ebd283cc5cd2cf5"},"url":"https://jobsearcher.com/jobs/85dba1662ebd283cc5cd2cf5"}}