We are a Biomechanics research team. We link human biology and anthropometrics to our unique technology performance in our devices - translating how people are built into how our products are designed. Our work spans the full spectrum from population-level human variability to the edge-case aggressors that challenge our devices most. We partner closely with Product Design, Industrial Design, and Advanced Research to make sure every decision is grounded in rigorous, human- centered data.

The role requires working at the intersection of biomechanics, sensing physics, software, and hardware - on a wide range of projects and with many cross- functional partners. Independent curiosity, a builder's instinct, and the ability to communicate complex technical findings to diverse audiences are essential. Ideal candidates are equally at home writing Python simulation tools, assembling a custom sensor rig, and presenting insights to a room of designers.

The Biomechanical Research Engineer works closely with Product Design, Industrial Design, and the Advanced Research teams to generate human-centered insights that directly shape product decisions.

Responsibilities
Investigating the relationship between biological features, anthropometrics, and technology performance in our devices, across both population distribution and various real-world aggressors and environmental conditions that stress device performance.
Developing Python-based simulation tools that enable the different teams to model and predict technology behavior relative to human variability.
Partnering with Advanced Research teams to define, develop, and execute end-to-end data-collection pipelines - from experimental protocol design through processing and analysis.
Translating complex, multi-dimensional datasets into clear, compelling visualizations that empower Product Design and Industrial Design teams to make confident product decisions.
Designing and building custom experimental setups from the ground up, integrating mechanical design with electronics across a broad range of sensing modalities, including 3D scanning, photogrammetry, IMUs, EEG, and strain gauges, Digital Image Correlation (DIC), and more.
Defining electrical engineering requirements and implementing control systems, algorithms, and data acquisition software to support experimental goals.
Leveraging embedded electronics platforms (Arduino, Raspberry Pi, ESP32, etc.) to build purpose-built measurement and data-collection rigs.
Communicating findings and recommendations clearly to partners with varying levels of technical expertise, from research engineers to industrial designers.