Senior Research Engineer, Structural Dynamics & Vibrations

In this role you will

• Develop mechanical sensing performance requirements. Select and evaluate new sensors for current and new mechanical sensing capabilities.

• Root-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.

• Characterize 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.

• Develop and own test methods to characterize and validate mechanical sensor performance across diverse and variable operating conditions.

• Develop 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).

• Develop signal quality observability for mechanical sensors: sensor trust metrics, quality scoring, and gating criteria for downstream uses of data.

• Mentor team members. Raise the technical rigor of experiments, analysis, and validation work across the team.

• Collaborate 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.

We 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.

• Sensor 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.

• Structural 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.

• Root-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.

• Hardware-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.

• Physical sensing research: researched new mechanical sensing capabilities using first-principles modeling, experiments, and sensor trade studies to evaluate feasibility and performance.

• Experience with deployed IoT fleets (tens of thousands of devices) and developing observability for long-term sensor performance — telemetry design, health metrics, calibration drift monitoring.

• Experience designing system validation plans with explicit acceptance criteria and building or owning repeatable test infrastructure.

• Embedded DSP exposure — applying DSP to real sensor signals on resource-constrained devices.

• Experience optimizing sampling and signal processing on constrained compute devices to reduce power and storage.

• Experience in sensor coexistence testing.