Biomechanical Research Engineer

Summary
At Apple, new ideas have a way of becoming phenomenal products, services, and

customer experiences. Imagine what you could do here. Bring passion and

dedication to your job, and there's no telling what you could accomplish.

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.

Description
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
  
  

• B.Sc. or M.Sc. in Mechanical Engineering, Biomedical Engineering, or a related field field
• Expertise in biomechanics, human factors, and/or anthropometrics, with the ability to connect biological and physiological variability to a physical device performance
• Strong Python proficiency for scientific computing, simulation, and tooling development
• Proven experience with data analysis and visualization, with a sharp ability to present insights in a clear and actionable format
• Hands-on experience designing and building end-to-end experimental hardware setups
• Familiarity with embedded electronics platforms (Arduino, Raspberry Pi, ESP32, etc.) and basic EE integration
• Experience with at least several of the following sensing modalities: IMUs, strain gauges, 3D scanning, photogrammetry, Digital Image Correlation (DIC), EEG
• Excellent verbal and written communication skills, with the ability to convey technical concepts to non-specialist audiences
• Highly self-directed, with a demonstrated capacity for independent learning in new technical domains
  
  

• 5+ years of industry or research experience in a relevant field
• Experience in complex, multi-disciplinary device development with human-factors interface research aspects
• Background in statistical modeling of population distributions or human physiological variability
• Proficiency in mechanical CAD tools (NX preferred) for fixture and experimental setup design
• Experience defining hardware or EE requirements in a cross-functional product development context
• Background in signal processing, algorithm development, or control systems
• Experience working within an advanced research or research-to-product pipeline