Wearable Biosensing R&D Engineer Intern

irhythmtech; San Francisco (CA); On-site; USD 34,000 - 48,000; Full time

Job summary

iRhythm Technologies, Inc. is seeking an engineering student for a full-time, six-month Co-op in San Francisco to contribute to wearable biosensor research and prototype development.

You will participate in feasibility studies, sensor evaluations, and data analysis within a regulated health-tech environment. The role emphasizes rapid prototyping, hypothesis-driven experimentation, and collaboration with a multidisciplinary team to translate clinical needs into engineering evidence and tangible

Qualifications

• Familiar with physiological parameters and sensing
• Experience applying hypothesis-driven experimental design
• Strong math/physics foundations, basic stats
• Detail-oriented and meticulous with lab records
• Excellent written and verbal communication; self-motivated and able to work with minimal supervision

Responsibilities

• Support early-stage research and feasibility for wearable sensing solutions
• Conduct user studies and collect data from human subjects
• Develop and execute test protocols for prototypes
• Apply signal processing/analysis techniques using Python or R
• Engage in rapid prototyping with evaluation kits and basic SolidWorks models
• Operate lab equipment (multimeters, oscilloscopes, power supplies)
• Learn to evaluate clinical needs and use cases in healthcare
• Collaborate with a technical team to prototype electromechanical hardware
• Contribute to data-driven decisions and potential IP generation

Skills

Python

Data analysis

Lab notebook

Written communication

Independent worker

Education

Pursuing a PhD or MS in biomedical, mechanical, electrical engineering

Tools

Python

R

SolidWorks

Job description

iRhythm Technologies, Inc. is seeking an engineering student for a full-time, six-month Co-op in San Francisco to contribute to wearable biosensor research and prototype development.

You will participate in feasibility studies, sensor evaluations, and data analysis within a regulated health-tech environment. The role emphasizes rapid prototyping, hypothesis-driven experimentation, and collaboration with a multidisciplinary team to translate clinical needs into engineering evidence and tangible