Signal Processing & Algorithms Engineering Intern

Location: Cambridge, MA
Duration: Spring or Summer 2027 (10+ weeks)

OrthoIQ is an MIT-founded medical technology startup developing intelligent surgical tools for orthopedic procedures. Our systems provide real-time sensing and feedback to surgeons, helping improve implant fixation, reduce complications, and improve surgical outcomes.

We are building a new class of smart orthopedic instrumentation, combining mechanical systems, sensing, and data to bring intelligence into the operating room.

We are seeking a Sensing & Signal Processing Engineering Intern to develop sensing and detection algorithms for our next-generation orthopedic surgical tools.

This is a highly experimental role spanning sensor selection, test design, data collection, signal processing, and algorithm development. You will work with physical prototypes and real sensor data to investigate methods for detecting clinically meaningful events during orthopedic impaction.

Select, characterize, and integrate force/load and other candidate sensors

Design experiments and collect synchronized sensor and ground-truth data

Develop data-acquisition and analysis workflows

Analyze signals using filtering, FFT/frequency-domain, time-domain, and other signal-processing techniques

Develop data-labeling and feature-engineering approaches

Explore statistical, ML, and classification methods for detecting implant seating and stop conditions

Validate algorithm accuracy, robustness, repeatability, and failure modes

Characterize computational requirements including sampling rate, memory, execution time, and latency

Develop analysis and prototyping tools in Python and/or MATLAB

Document experimental methods, results, and design recommendations

Pursuing or recently completed a BS/MS in Electrical Engineering, Biomedical Engineering, Robotics, Computer Engineering, or a related field

Coursework or project experience in signal processing, controls, instrumentation, data science, or machine learning

Experience with Python and/or MATLAB

Familiarity with sensors and data-acquisition systems

Experience analyzing experimental time-series data preferred

Hands-on prototyping or laboratory experience

Familiarity with microcontrollers or embedded systems is a plus, but not required

Comfortable independently solving open-ended technical problems in an early-stage startup environment

Ownership of sensing R&D that directly informs product development

Experience developing algorithms from raw physical sensor data

Hands-on experience designing and running experiments on medical-device prototypes

Exposure to regulated medical-device development

Experience translating research algorithms into requirements for embedded implementation

Close collaboration with experienced engineers and orthopedic surgeons

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Our main product is an orthopedic automatic hammer with an integrated sensor that tells the surgeon when to stop hammering. Right now they judge when to stop hammering based on feel, but overhammering can cause bone fractures and underhammering causes the implant to loosen over time.

Interns will help solve real engineering challenges in mechanism design, prototyping, component selection, thermal management, and reducing weight and recoil.

We're integrating sensors to measure what happens during each impact and exploring whether those signals can identify when an implant has reached stable fixation. Interns may build test rigs and data-acquisition systems, run experiments, and analyze mechanical and sensor data.

Surgical devices have to work reliably across different implants, bone conditions, loads, and repeated use. Our device must be manufacturable, sterilizable, reliable, serviceable, and intuitive to use in the operating room.

Interns will contribute to DFM/DFA, reliability and verification testing, design iteration, and the engineering decisions required to move from prototype to production.

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