Mark Bremer, Developer in Cambridge, ON, Canada
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Mark Bremer

Verified Expert  in Engineering

Embedded C and C++ Developer

Cambridge, ON, Canada

Toptal member since August 31, 2021

Bio

Mark has 8+ years of experience developing embedded software in C and C++ and industrial automation software using LabVIEW and Python. He has helped companies develop a wide range of products, including medical devices, IoT sensors, and energy monitoring systems. Most of his embedded experience has been with ARM processors, either Cortex-M (using an RTOS-like FreeRTOS) or Cortex-A (using embedded Linux).

Portfolio

Prolucid Technologies
Embedded C, Embedded C++, LabVIEW, Machine Learning, Python, TensorFlow

Experience

  • C - 10 years
  • Linux - 10 years
  • ARM - 8 years
  • Embedded C - 8 years
  • Software Engineering - 8 years
  • LabVIEW - 8 years
  • Certified LabVIEW Architect - 5 years
  • Python - 3 years

Availability

Part-time

Preferred Environment

Windows 10, Linux, ARM, C, C++, Python, LabVIEW

The most amazing...

...product I've helped create is a medical device used to help stroke or spinal cord injury patients regain the use of their muscles.

Work Experience

Project Lead, Systems Architect

2013 - 2021
Prolucid Technologies
  • Led a team to develop a handheld blood diagnostic device using vision processing on FPGA and microfluidic pumping.
  • Developed an automated assembly line vision system to detect defects in automotive parts using machine learning.
  • Led a team to develop medical device software that helps patients with spinal cord injuries and stroke victims to regain the use of their muscles.
Technologies: Embedded C, Embedded C++, LabVIEW, Machine Learning, Python, TensorFlow

Blood Testing Medical Device

A medical device that analyzed a blood sample to detect specific markers in the blood. I co-developed the handheld device and the firmware that was developed for an ARM Cortex-A processor that included an FPGA.

The firmware controlled the flow of blood through the device. Focused optics allowed a camera to view the blood sample and controlled a laser that enabled targets in the blood to appear in the camera images. We also developed several user interface peripherals (display, keyboard, and buttons).

I designed and developed the image processing algorithms needed to track and count the marked cells in the video of the blood sample, which was partially implemented on FPGA to allow us to process at the required frame rate. I also developed a custom user interface library to support the small form factor black and white display used.

Overall, this project was a great combination of learning new tools and frameworks, advanced algorithm design, and low-level embedded device interfacing. Most-of-all, I was able to work on a device that could have a real positive effect on the world.
2011 - 2014

Master's Degree in Software Engineering

McMaster University - Hamilton, Ontario, CA

2006 - 2011

Bachelor's Degree in Mechatronics Engineering

McMaster University - Hamilton, Ontario, CA

JULY 2020 - PRESENT

Professional Engineer

Professional Engineers of Ontario

FEBRUARY 2020 - FEBRUARY 2024

Certified LabVIEW Architect

National Instruments (NI)

Libraries/APIs

TensorFlow

Tools

LabVIEW

Languages

C, Embedded C, Python, Embedded C++, C++

Platforms

Linux

Other

Software Engineering, Certified LabVIEW Architect, ARM, Engineering, Machine Learning, Device Drivers

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