Research Engineer, Mechanical

We are seeking a Research Engineer to join our Physical R&D team. You will develop and operate the analytical infrastructure for a new product that expands Gridware’s edge grid monitoring and observability platform.

This role is primarily computational. You will analyze novel measurements across our deployed fleet, build tools and workflows for investigation and interpretation, and help operationalize new measurement products for delivery to utility customers. You will need deep physical intuition for the behavior of mechanical systems to interpret what the measurements mean in the real world, guide how we validate them, and identify where performance limitations exist.

• MS or PhD in Mechanical Engineering, Civil/Structural Engineering, Engineering Mechanics, or a closely related field and 2+ years of relevant industry experience.

• Strong fundamentals in solid mechanics: beam theory, stress analysis, structural loading. Able to reason from first principles about what physical conditions produce the stresses and deflections we measure.

• Scientific computing: comfortable building analysis pipelines in Python, MATLAB, or equivalent to investigate and report system performance across large datasets.

• Experience with exploratory data analysis—identifying patterns, anomalies, and cohort-level behavior in noisy real-world data.

• Clear technical communication and documentation skills.

• Comfortable working on ambiguous technical problems and learning new domains quickly.

You do not need to match every area below. Strong candidates will usually bring depth in two or more of these areas.

• Sensor data interpretation for physical systems: experience using sensor signals to draw conclusions about the physical state of a system—developing metrics, identifying signal features, or building monitoring workflows that translate raw measurements into actionable information.

• Statistical analysis of physical systems: experience with extreme value statistics, reliability analysis, survival analysis, or probabilistic methods applied to structural or mechanical systems.

• Fleet-scale data analysis and data engineering: experience working with sensor data from large deployed populations—including SQL-based analysis on structured telemetry, population-level trend identification, and data quality assessment across thousands of units.

• Validation and test design: experience designing validation studies, defining acceptance criteria, and systematically characterizing measurement system performance.

• Familiarity with GIS tools or spatial analysis for infrastructure data.

• Experience operationalizing analytical workflows into production systems (dashboards, automated reporting, alerting).