{"schemaVersion":"jobsearcher.job.v1","id":"e4ffe409f14753a1f5896b05","url":"https://jobsearcher.com/jobs/e4ffe409f14753a1f5896b05","canonicalUrl":"https://jobsearcher.com/jobs/e4ffe409f14753a1f5896b05","title":"Senior Research Engineer, Structural Dynamics & Vibrations","description":"About Gridware\nGridware is a San Francisco‑based technology company dedicated to protecting and enhancing the electrical grid. Gridware pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware’s advanced Active Grid Response platform uses high‑precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate‑tech and Silicon Valley investors. For more information, visit www.Gridware.io.\n\nRole Description\nWe are seeking a creative, hands‑on Senior Mechanical Research Engineer with significant vibration and dynamics experience to lead complex mechanical sensing problems on edge grid intelligence products with real‑world impact.\n\nYou will become an expert in how our grid sensor signals — accelerometer, IMU, and other mechanical‑measurement signals — behave in the real world across diverse infrastructure. You will investigate sensing performance via exploratory data analysis, dynamics modeling coupled with bench and full‑scale testing. You will also support design improvements, and validate improvements using test infrastructure you develop. You will define mechanical sensing requirements, develop measurement‑chain improvements, and help mature new mechanical sensing capabilities.\n\nThe focus is on understanding the mechanical phenomena that affect the grid, including measurement performance, validation, and technology transfer, rather than product design or implementation.\n\nResponsibilities\n\nDevelop mechanical sensing performance requirements. Select and evaluate new sensors for current and new mechanical sensing capabilities.\n\nRoot‑cause mechanical sensor signal issues from fleet to bench: use fleet telemetry (time‑series + metadata) to isolate failure patterns, modes and signatures, test hypotheses via dynamics modeling and benchtop reproduction, contribute to design solutions, and partner with HW, FW, and SW engineering to implement them.\n\nCharacterize and validate how diverse infrastructure types — different pole materials, geometries, and equipment configurations — affect mechanical signal behavior. Translate findings into design guidance, device installation requirements, monitoring and data aggregation methods.\n\nDevelop and own test methods to characterize and validate mechanical sensor performance across diverse and variable operating conditions.\n\nDevelop hardware‑in‑the‑loop test infrastructure to reproduce real‑world mechanical phenomena Gridware technology detects. Run hardware‑in‑the‑loop tests to validate changes to our tech stack (from phenomena > hardware > automation > customer).\n\nDevelop signal quality observability for mechanical sensors: sensor trust metrics, quality scoring, and gating criteria for downstream uses of data.\n\nMentor team members. Raise the technical rigor of experiments, analysis, and validation work across the team.\n\nCollaborate closely with product managers, data scientists, automation engineers, SW/HW/FW engineers, as well as non‑technical teams such as customer success, field teams, and manufacturing.\n\nRequired Skills\n\nSenior‑level experience: PhD in Mechanical Engineering, Aerospace Engineering, Engineering Mechanics, or a closely related field plus 3+ years of relevant industry experience or MS in one of those fields plus 6+ years of relevant industry experience in owning open‑ended, research‑driven mechanical sensing or signal‑quality problems.\n\nStrong fundamentals in vibrations, dynamics, and structural response, with the ability to connect those fundamentals to real signals — extracting physical meaning through modal analysis, impact identification, source separation, frequency‑domain feature extraction, and transient classification.\n\nTrack record of owning ambiguous sensing, signal‑quality, or measurement‑performance problems from characterizing through validation.\n\nScientific computing: comfortable writing analysis pipelines in Python, MATLAB, or equivalent to investigate and report system performance to broad audiences.\n\nExperience collecting high‑quality mechanical measurements: have built and run custom measurement setups using accelerometers, IMUs, force/strain transducers, and standard lab instrumentation (DAQ and related tools).\n\nStrong technical judgment, communication, and cross‑functional collaboration.\n\nExperience leading technically complex work with multiple stakeholders and deadlines.\n\nRelevant Depth Areas\nWe do not expect every senior candidate to be equally deep in every area below. Strong candidates will usually bring deep experience in several of these areas.\n\nSensor characterization and validation: led mechanical sensor performance evaluation from characterization through test method development. Experience developing performance requirements and testing or validating sensing systems against those requirements.\n\nStructural dynamics on real infrastructure: modal analysis, operational modal analysis, or experimental dynamics on civil/industrial structures with realistic boundary conditions, equipment loads, and environmental coupling.\n\nRoot‑cause sensor signal issues: track record investigating and solving signal/noise issues — identifying issues through exploratory data analysis, reproducing in simulation and on the bench, and implementing solutions.\n\nHardware‑in‑the‑loop test infrastructure: designed and built mechanical or electromechanical HIL rigs to reproduce real‑world phenomena and validate sensor or algorithm changes pre‑release.\n\nPhysical sensing research: researched new mechanical sensing capabilities using first‑principles modeling, experiments, and sensor trade studies to evaluate feasibility and performance.\n\nBonus Skills\n\nExperience with deployed IoT fleets (tens of thousands of devices) and developing observability for long‑term sensor performance — telemetry design, health metrics, calibration drift monitoring.\n\nExperience designing system validation plans with explicit acceptance criteria and building or owning repeatable test infrastructure.\n\nEmbedded DSP exposure — applying DSP to real sensor signals on resource‑constrained devices.\n\nExperience optimizing sampling and signal processing on constrained compute devices to reduce power and storage.\n\nExperience in sensor coexistence testing.\n\n$175,000 - $200,000 a year\n\nThis describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply!\n\nBenefits\n\nHealth, Dental & Vision (Gold and Platinum with some providers plans fully covered)\n\nPaid parental leave\n\nAlternating day off (every other Monday)\n\nOff the Grid, a two week per year paid break for all employees.\n\nCommuter allowance\n\nCompany‑paid training\n\n#J-18808-Ljbffr","company":"Gridware Technologies","rawCompany":"gridware technologies","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-06-20T04:44:14.754Z","occupations":[{"code":"17-2141.00","title":"Mechanical Engineers","slug":"mechanical-engineers"},{"code":"17-2199.00","title":"Engineers, All Other","slug":"engineers-all-other"},{"code":"17-2199.05","title":"Mechatronics Engineers","slug":"mechatronics-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":"Senior Research Engineer, Structural Dynamics & Vibrations","description":"About Gridware\nGridware is a San Francisco‑based technology company dedicated to protecting and enhancing the electrical grid. Gridware pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware’s advanced Active Grid Response platform uses high‑precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate‑tech and Silicon Valley investors. For more information, visit www.Gridware.io.\n\nRole Description\nWe are seeking a creative, hands‑on Senior Mechanical Research Engineer with significant vibration and dynamics experience to lead complex mechanical sensing problems on edge grid intelligence products with real‑world impact.\n\nYou will become an expert in how our grid sensor signals — accelerometer, IMU, and other mechanical‑measurement signals — behave in the real world across diverse infrastructure. You will investigate sensing performance via exploratory data analysis, dynamics modeling coupled with bench and full‑scale testing. You will also support design improvements, and validate improvements using test infrastructure you develop. You will define mechanical sensing requirements, develop measurement‑chain improvements, and help mature new mechanical sensing capabilities.\n\nThe focus is on understanding the mechanical phenomena that affect the grid, including measurement performance, validation, and technology transfer, rather than product design or implementation.\n\nResponsibilities\n\nDevelop mechanical sensing performance requirements. Select and evaluate new sensors for current and new mechanical sensing capabilities.\n\nRoot‑cause mechanical sensor signal issues from fleet to bench: use fleet telemetry (time‑series + metadata) to isolate failure patterns, modes and signatures, test hypotheses via dynamics modeling and benchtop reproduction, contribute to design solutions, and partner with HW, FW, and SW engineering to implement them.\n\nCharacterize and validate how diverse infrastructure types — different pole materials, geometries, and equipment configurations — affect mechanical signal behavior. Translate findings into design guidance, device installation requirements, monitoring and data aggregation methods.\n\nDevelop and own test methods to characterize and validate mechanical sensor performance across diverse and variable operating conditions.\n\nDevelop hardware‑in‑the‑loop test infrastructure to reproduce real‑world mechanical phenomena Gridware technology detects. Run hardware‑in‑the‑loop tests to validate changes to our tech stack (from phenomena > hardware > automation > customer).\n\nDevelop signal quality observability for mechanical sensors: sensor trust metrics, quality scoring, and gating criteria for downstream uses of data.\n\nMentor team members. Raise the technical rigor of experiments, analysis, and validation work across the team.\n\nCollaborate closely with product managers, data scientists, automation engineers, SW/HW/FW engineers, as well as non‑technical teams such as customer success, field teams, and manufacturing.\n\nRequired Skills\n\nSenior‑level experience: PhD in Mechanical Engineering, Aerospace Engineering, Engineering Mechanics, or a closely related field plus 3+ years of relevant industry experience or MS in one of those fields plus 6+ years of relevant industry experience in owning open‑ended, research‑driven mechanical sensing or signal‑quality problems.\n\nStrong fundamentals in vibrations, dynamics, and structural response, with the ability to connect those fundamentals to real signals — extracting physical meaning through modal analysis, impact identification, source separation, frequency‑domain feature extraction, and transient classification.\n\nTrack record of owning ambiguous sensing, signal‑quality, or measurement‑performance problems from characterizing through validation.\n\nScientific computing: comfortable writing analysis pipelines in Python, MATLAB, or equivalent to investigate and report system performance to broad audiences.\n\nExperience collecting high‑quality mechanical measurements: have built and run custom measurement setups using accelerometers, IMUs, force/strain transducers, and standard lab instrumentation (DAQ and related tools).\n\nStrong technical judgment, communication, and cross‑functional collaboration.\n\nExperience leading technically complex work with multiple stakeholders and deadlines.\n\nRelevant Depth Areas\nWe do not expect every senior candidate to be equally deep in every area below. Strong candidates will usually bring deep experience in several of these areas.\n\nSensor characterization and validation: led mechanical sensor performance evaluation from characterization through test method development. Experience developing performance requirements and testing or validating sensing systems against those requirements.\n\nStructural dynamics on real infrastructure: modal analysis, operational modal analysis, or experimental dynamics on civil/industrial structures with realistic boundary conditions, equipment loads, and environmental coupling.\n\nRoot‑cause sensor signal issues: track record investigating and solving signal/noise issues — identifying issues through exploratory data analysis, reproducing in simulation and on the bench, and implementing solutions.\n\nHardware‑in‑the‑loop test infrastructure: designed and built mechanical or electromechanical HIL rigs to reproduce real‑world phenomena and validate sensor or algorithm changes pre‑release.\n\nPhysical sensing research: researched new mechanical sensing capabilities using first‑principles modeling, experiments, and sensor trade studies to evaluate feasibility and performance.\n\nBonus Skills\n\nExperience with deployed IoT fleets (tens of thousands of devices) and developing observability for long‑term sensor performance — telemetry design, health metrics, calibration drift monitoring.\n\nExperience designing system validation plans with explicit acceptance criteria and building or owning repeatable test infrastructure.\n\nEmbedded DSP exposure — applying DSP to real sensor signals on resource‑constrained devices.\n\nExperience optimizing sampling and signal processing on constrained compute devices to reduce power and storage.\n\nExperience in sensor coexistence testing.\n\n$175,000 - $200,000 a year\n\nThis describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply!\n\nBenefits\n\nHealth, Dental & Vision (Gold and Platinum with some providers plans fully covered)\n\nPaid parental leave\n\nAlternating day off (every other Monday)\n\nOff the Grid, a two week per year paid break for all employees.\n\nCommuter allowance\n\nCompany‑paid training\n\n#J-18808-Ljbffr","datePosted":"2026-06-20T04:44:14.754Z","dateModified":"2026-06-20T04:44:14.754Z","hiringOrganization":{"@type":"Organization","name":"Gridware Technologies","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"e4ffe409f14753a1f5896b05"},"url":"https://jobsearcher.com/jobs/e4ffe409f14753a1f5896b05"}}