{"schemaVersion":"jobsearcher.job.v1","id":"c0e96d0f4ffb95cc52d59fad","url":"https://jobsearcher.com/jobs/c0e96d0f4ffb95cc52d59fad","canonicalUrl":"https://jobsearcher.com/jobs/c0e96d0f4ffb95cc52d59fad","title":"Sensor Validation Engineer","description":"Job Requirements\n\nWho We Are:\n\nQuest Global delivers world-class end-to-end engineering solutions by leveraging our deep industry knowledge and digital expertise. By bringing together technologies and industries, alongside the contributions of diverse individuals and their areas of expertise, we are able to solve problems better, faster. This multi-dimensional approach enables us to solve the most critical and large-scale challenges across the aerospace & defense, automotive, energy, hi-tech, healthcare, medical devices, rail and semiconductor industries.\n\nWe are looking for humble geniuses, who believe that engineering has the potential to make the impossible possible; innovators, who are not only inspired by technology and innovation, but also perpetually driven to design, develop, and test as a trusted partner for Fortune 500 customers. As a team of remarkably diverse engineers, we recognize that what we are really engineering is a brighter future for us all. If you want to contribute to meaningful work and be part of an organization that truly believes when you win, we all win, and when you fail, we all learn, then we’re eager to hear from you.\n\nWe are looking for a Sensor Validation Engineer to own validation of tamper detection sensing on smart glasses products, with the flexibility to extend into camera and LED luminance validation as program needs evolve. You will define validation methodology, build and maintain test automation, run characterization and regression testing, and drive sensor- and optics-related issues to root cause alongside hardware and software partners.\n\nThe achievers and courageous challenge-crushers we seek have the following characteristics and skills:\n\nWhat you will do\n\nOwn end-to-end validation of tamper detection: define test plans, acceptance criteria, corner cases, and regression coverage.\n\nDevelop, extend, and maintain Python-based test automation; understand existing scripts and add new capability rather than rebuilding from scratch.\n\nBuild supporting shell/batch tooling for test setup, device control, data collection, and post-processing.\n\nExecute device-level testing using ADB and other on-device instrumentation.\n\nPerform optical measurements using industry-standard luminance and lux meters; maintain measurement repeatability and setup calibration.\n\nExtend scope to other domains such as camera and LED luminance validation as the program requires.\n\nAnalyze test data with Python (pandas, numpy, OpenCV) and generate informative reports that pair data with interpretation, insights, and clear recommendations.\n\nLeverage AI-assisted tooling to improve validation throughput — test script generation, log and failure triage, anomaly detection in measurement data, and report drafting — while retaining engineering ownership of results and conclusions.\n\nDocument validation methodology in detail so tests are reproducible across sites and teams.\n\nTroubleshoot sensor and optics issues, partnering with hardware, optics, and software teams to narrow down root cause.\n\nSpecify test specifications and the equipment required for proper validation coverage.\n\nWork Experience\n\nWhat You Will Bring:\n\nOwn end-to-end validation of tamper detection: define test plans, acceptance criteria, corner cases, and regression coverage.\n\nDevelop, extend, and maintain Python-based test automation; understand existing scripts and add new capability rather than rebuilding from scratch.\n\nBuild supporting shell/batch tooling for test setup, device control, data collection, and post-processing.\n\nExecute device-level testing using ADB and other on-device instrumentation.\n\nPerform optical measurements using industry-standard luminance and lux meters; maintain measurement repeatability and setup calibration.\n\nExtend scope to other domains such as camera and LED luminance validation as the program requires.\n\nAnalyze test data with Python (pandas, numpy, OpenCV) and generate informative reports that pair data with interpretation, insights, and clear recommendations.\n\nLeverage AI-assisted tooling to improve validation throughput — test script generation, log and failure triage, anomaly detection in measurement data, and report drafting — while retaining engineering ownership of results and conclusions.\n\nDocument validation methodology in detail so tests are reproducible across sites and teams.\n\nTroubleshoot sensor and optics issues, partnering with hardware, optics, and software teams to narrow down root cause.\n\nSpecify test specifications and the equipment required for proper validation coverage.\n\nMinimum Qualifications\n\nBachelor's degree in Electrical/Electronics Engineering, or equivalent with formal training in optics.\n\n5–10 years in a system validation role for consumer electronics or a related field.\n\nDemonstrated understanding of ambient light sensing (ALS) and its validation.\n\nProficiency in Python for test automation and data analysis (pandas, numpy, OpenCV), plus shell/batch scripting.\n\nHands-on experience with ADB and device-level debugging.\n\nAbility to define test specs and select appropriate test equipment.\n\nComfortable working across both macOS and Windows.\n\nExperience in technical documentation and test report generation.\n\nStrong written and verbal communication; able to convey complex technical information to technical and non-technical audiences.\n\nStrong analytical and problem-solving skills.\n\nPreferred Qualifications\n\nHands-on experience with industry-standard luminance and lux meters and optical test benches.\n\nPrior experience validating tamper detection, proximity, or capacitive/optical sensing systems.\n\nCamera validation experience (image quality, exposure, or photometric measurement).\n\nExperience applying AI-based tools to validation work — accelerating script development, automating log and failure triage, summarizing large validation datasets, or assisting anomaly detection.\n\nTrack record of independently finding and adopting new libraries or tools to solve measurement problems.\n\nDemonstrated interest in cross-skilling and upskilling across adjacent sensing domain\n\nPay Range: $115,000 - $145,000\n\nCompensation decisions are made based on factors including experience, skills, education, and other job-related factors, in accordance with our internal pay structure. We also offer a comprehensive benefits package, including health insurance, paid time off, and retirement plan.\n\nWork Requirements:\n\nThis role is considered an on-site position located in Sunnyvale, CA\n\nYou must be able to commute to and from the location with your own transportation arrangements to meet the required working hours.\n\nBenefits\n\nBenefits\n\n• 401(k)\n\n• 401(k) matching\n\n• Dental insurance\n\n• Health insurance\n\n• Life insurance\n\n• Paid time off\n\n• Referral program\n\n• Vision insurance\n\n• Short/Long Term Disability","company":"Quest Global","rawCompany":"quest global","city":"Sunnyvale","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-10-02T07:57:11.319Z","occupations":[{"code":"17-2112.02","title":"Validation Engineers","slug":"validation-engineers"},{"code":"15-1253.00","title":"Software Quality Assurance Analysts and Testers","slug":"software-quality-assurance-analysts-and-testers"},{"code":"19-4099.01","title":"Quality Control Analysts","slug":"quality-control-analysts"}],"industries":[{"code":"334513","title":"Instruments and Related Products Manufacturing for Measuring, Displaying, and Controlling Industrial Process Variables","slug":"instruments-and-related-products-manufacturing-for-measuring-displaying-and-controlling-industrial-process-variables"},{"code":"334519","title":"Other Measuring and Controlling Device Manufacturing","slug":"other-measuring-and-controlling-device-manufacturing"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Sensor Validation Engineer","description":"Job Requirements\n\nWho We Are:\n\nQuest Global delivers world-class end-to-end engineering solutions by leveraging our deep industry knowledge and digital expertise. By bringing together technologies and industries, alongside the contributions of diverse individuals and their areas of expertise, we are able to solve problems better, faster. This multi-dimensional approach enables us to solve the most critical and large-scale challenges across the aerospace & defense, automotive, energy, hi-tech, healthcare, medical devices, rail and semiconductor industries.\n\nWe are looking for humble geniuses, who believe that engineering has the potential to make the impossible possible; innovators, who are not only inspired by technology and innovation, but also perpetually driven to design, develop, and test as a trusted partner for Fortune 500 customers. As a team of remarkably diverse engineers, we recognize that what we are really engineering is a brighter future for us all. If you want to contribute to meaningful work and be part of an organization that truly believes when you win, we all win, and when you fail, we all learn, then we’re eager to hear from you.\n\nWe are looking for a Sensor Validation Engineer to own validation of tamper detection sensing on smart glasses products, with the flexibility to extend into camera and LED luminance validation as program needs evolve. You will define validation methodology, build and maintain test automation, run characterization and regression testing, and drive sensor- and optics-related issues to root cause alongside hardware and software partners.\n\nThe achievers and courageous challenge-crushers we seek have the following characteristics and skills:\n\nWhat you will do\n\nOwn end-to-end validation of tamper detection: define test plans, acceptance criteria, corner cases, and regression coverage.\n\nDevelop, extend, and maintain Python-based test automation; understand existing scripts and add new capability rather than rebuilding from scratch.\n\nBuild supporting shell/batch tooling for test setup, device control, data collection, and post-processing.\n\nExecute device-level testing using ADB and other on-device instrumentation.\n\nPerform optical measurements using industry-standard luminance and lux meters; maintain measurement repeatability and setup calibration.\n\nExtend scope to other domains such as camera and LED luminance validation as the program requires.\n\nAnalyze test data with Python (pandas, numpy, OpenCV) and generate informative reports that pair data with interpretation, insights, and clear recommendations.\n\nLeverage AI-assisted tooling to improve validation throughput — test script generation, log and failure triage, anomaly detection in measurement data, and report drafting — while retaining engineering ownership of results and conclusions.\n\nDocument validation methodology in detail so tests are reproducible across sites and teams.\n\nTroubleshoot sensor and optics issues, partnering with hardware, optics, and software teams to narrow down root cause.\n\nSpecify test specifications and the equipment required for proper validation coverage.\n\nWork Experience\n\nWhat You Will Bring:\n\nOwn end-to-end validation of tamper detection: define test plans, acceptance criteria, corner cases, and regression coverage.\n\nDevelop, extend, and maintain Python-based test automation; understand existing scripts and add new capability rather than rebuilding from scratch.\n\nBuild supporting shell/batch tooling for test setup, device control, data collection, and post-processing.\n\nExecute device-level testing using ADB and other on-device instrumentation.\n\nPerform optical measurements using industry-standard luminance and lux meters; maintain measurement repeatability and setup calibration.\n\nExtend scope to other domains such as camera and LED luminance validation as the program requires.\n\nAnalyze test data with Python (pandas, numpy, OpenCV) and generate informative reports that pair data with interpretation, insights, and clear recommendations.\n\nLeverage AI-assisted tooling to improve validation throughput — test script generation, log and failure triage, anomaly detection in measurement data, and report drafting — while retaining engineering ownership of results and conclusions.\n\nDocument validation methodology in detail so tests are reproducible across sites and teams.\n\nTroubleshoot sensor and optics issues, partnering with hardware, optics, and software teams to narrow down root cause.\n\nSpecify test specifications and the equipment required for proper validation coverage.\n\nMinimum Qualifications\n\nBachelor's degree in Electrical/Electronics Engineering, or equivalent with formal training in optics.\n\n5–10 years in a system validation role for consumer electronics or a related field.\n\nDemonstrated understanding of ambient light sensing (ALS) and its validation.\n\nProficiency in Python for test automation and data analysis (pandas, numpy, OpenCV), plus shell/batch scripting.\n\nHands-on experience with ADB and device-level debugging.\n\nAbility to define test specs and select appropriate test equipment.\n\nComfortable working across both macOS and Windows.\n\nExperience in technical documentation and test report generation.\n\nStrong written and verbal communication; able to convey complex technical information to technical and non-technical audiences.\n\nStrong analytical and problem-solving skills.\n\nPreferred Qualifications\n\nHands-on experience with industry-standard luminance and lux meters and optical test benches.\n\nPrior experience validating tamper detection, proximity, or capacitive/optical sensing systems.\n\nCamera validation experience (image quality, exposure, or photometric measurement).\n\nExperience applying AI-based tools to validation work — accelerating script development, automating log and failure triage, summarizing large validation datasets, or assisting anomaly detection.\n\nTrack record of independently finding and adopting new libraries or tools to solve measurement problems.\n\nDemonstrated interest in cross-skilling and upskilling across adjacent sensing domain\n\nPay Range: $115,000 - $145,000\n\nCompensation decisions are made based on factors including experience, skills, education, and other job-related factors, in accordance with our internal pay structure. We also offer a comprehensive benefits package, including health insurance, paid time off, and retirement plan.\n\nWork Requirements:\n\nThis role is considered an on-site position located in Sunnyvale, CA\n\nYou must be able to commute to and from the location with your own transportation arrangements to meet the required working hours.\n\nBenefits\n\nBenefits\n\n• 401(k)\n\n• 401(k) matching\n\n• Dental insurance\n\n• Health insurance\n\n• Life insurance\n\n• Paid time off\n\n• Referral program\n\n• Vision insurance\n\n• Short/Long Term Disability","datePosted":"2026-10-02T07:57:11.319Z","dateModified":"2026-10-02T07:57:11.319Z","hiringOrganization":{"@type":"Organization","name":"Quest Global","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Sunnyvale","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"c0e96d0f4ffb95cc52d59fad"},"url":"https://jobsearcher.com/jobs/c0e96d0f4ffb95cc52d59fad"}}