Senior Systems Engineer, Sensors

**About Gridware** Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We 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, please visit [](http://www.gridware.io/). ### Role Description We are seeking a creative, hands-on Senior Systems Engineer to lead ambiguous sensing and measurement problems with real-world impact. You will become an expert in how our grid sensor signals behave in the real world. You will investigate sensing issues and performance via exploratory data analysis, hardware simulation, and bench debugging, design improvements, and validate improvements using test infrastructure you develop. You will define sensing requirements, develop measurement-chain improvements, and help mature new sensing capabilities. This position focuses on measurement performance, validation, and technology transfer rather than product design and implementation. ### Responsibilities - Develop measurement performance requirements. Select and evaluate new sensors for current and new sensing capabilities. - Root-cause sensor signal issues from fleet to bench: use fleet telemetry (time-series + metadata) to isolate cohorts and failure signatures, test hypotheses via circuit simulation and benchtop reproduction, drive fixes design solutions, and partner with HW and FW engineering to implement them. - Design and validate measurement chain changes to improve physical phenomena observability. - Downsize on-device data. Develop signal compression techniques, selective data storage decisions, and sampling rate reduction strategies. - Develop and own test methods to characterize and validate sensor performance. - Develop hardware-in-the-loop test infrastructure to reproduce the real-world physical phenomena Gridware technology detects. Run hardware-in-the-loop tests to validate changes to our tech stack (HW, phenomena detection algorithms). - Mentor team members. Raise the technical rigor of experiments, analysis, and validation work. - Collaborate closely with product managers, data scientists, and SW/HW/FW engineers. ### Required Skills - MS in Electrical Engineering, Physics, or a related field with 4+ years of relevant industry experience, or PhD with 1+ year of relevant industry experience. - Track record of owning ambiguous sensing, signal-quality, or measurement-performance problems from framing through validation. - Scientific computing: comfortable writing analysis pipelines in Python, MATLAB, or equivalent to investigate and report system performance. - Experience collecting high-quality electrical measurements: have built and run custom measurement setups using standard lab instrumentation (scope/DAQ and related tools). - Strong technical judgment, communication, and cross-functional collaboration. - Experience leading technically complex work with multiple stakeholders and deadlines. - Strong fundamentals in electromagnetics. **Relevant Depth Areas** - Sensing & measurement: Sensor characterization, performance requirements, signal/noise investigation, test development, and validation of sensing systems. - Signal processing & embedded systems: DSP on real-world sensor signals, including sampling, filtering, compression, and embedded implementation. - Modeling & experimentation: First-principles modeling, circuit simulation (SPICE or similar), and hands-on experiments to understand physical phenomena and improve sensing performance. ### Bonus Skills - Design and automate validation: have designed system validation plans with explicit acceptance criteria. Have built or owned repeatable test infrastructure. - Experience with deployed IoT fleets (tens of thousands of devices) and developing “observability for sensor performance” e.g. telemetry design, health metrics, calibration drift monitoring. - Experience optimizing sampling and signal processing on constrained compute devices to reduce power and storage.