Kaden Suderman

Computer Vision & Field Engineer

Physical AI · Industrial Vision · Edge Deployment

Email GitHub ↗ LinkedIn ↗ Open PDF

Experience

Roboflow

Nov 2025 - Sep 2026

Built and deployed real-time industrial computer vision pipelines covering annotation, training, tracking, inference, and application outputs.
Supported onsite deployments with Fortune 500 manufacturers and worked directly with engineering and Center of Excellence teams.
Provisioned NVIDIA Jetson systems, specified industrial cameras and edge compute, and troubleshot Linux, networking, containers, and customer environments.
Built an equipment inventory and procurement portal tracking more than $1M in hardware.

Boston Scientific

Jan - Aug 2023

Developed classical vision systems for label detection on medical-device manufacturing lines using Cognex, Keyence, OpenCV, scikit-image, and NumPy.
Set up and tested industrial cameras and lighting, then automated the sorting of more than 100GB of image data with Python.

Analog Devices

May - Aug 2022

Programmed Arduino and ESP32 systems, flashed firmware with PlatformIO, and debugged hardware over UART and JTAG.
Built a Python image-conversion tool for automated batch processing in hardware simulations.

Real-time waste classification from camera input through offline inference, tracking, metrics, and Streamlit output. Deployed on a Raspberry Pi 4B.

Edge-to-cloud object segmentation using Raspberry Pi, remote GPU inference, YOLOv8x-seg, FastSAM, BLE, and networked image processing.

Master of Engineering, Electronic & Computer Engineering, 2024

First Class Honors, GPA 3.85

Bachelor of Engineering, 2023

Analog Devices Elite Scholarship, 2022

Languages: Python, C, C++, Java, SQL

Vision: OpenCV, PyTorch, TensorFlow, YOLO, ONNX, TensorRT, Roboflow

Industrial: Basler, LUCID, Cognex, Keyence, SICK, Zebra

Deployment: NVIDIA Jetson, Raspberry Pi, Linux, Docker, SSH, Tailscale