Mobile app Developer (Paid Internship) in Fort Atkinson, Wisconsin at CTPS / Complete TransPack Solutions
NewSalary: $30.00 - $30.00/hrJob Function: Information Technology
CTPS / Complete TransPack Solutions
Fort Atkinson, Wisconsin, 53538, United States
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Job Description
Duties & Responsibilities:
Build a functional prototype of a mobile warehouse utility app designed to instantly count stacked warehouse supplies using on
device artificial intelligence.
Train a lightweight, commercially viable custom object detection model (using frameworks like YOLOv8, YOLOv11, YOLO-NAS, or
YOLOX) to recognize pallets, top frames, and layer pads across varying lighting conditions and angles.
Prepare and organize data by setting up a lightweight annotating workflow (e.g., Roboflow or CVAT) to label a dataset of 300–500
images of inventory.
Export and optimize the trained model (via CoreML or TensorFlow Lite) to ensure it can run locally and offline inside the mobile
application.
Build a simple, clean user interface (UI) that integrates the model to display real-time counting overlays and bounding boxes on a
live camera feed or uploaded photo.
Co-work directly with one of the company owners to develop, iterate, and test the prototype.
Skills and Knowledge preferred:
Solid foundations and strong skills in Python for training pipelines.
Experience with computer vision libraries (OpenCV, PyTorch, or TensorFlow) and 1+ years of experience working with the YOLO
architecture.
Proven experience embedding machine learning models onto edge devices, with knowledge of leveraging hardware acceleration
(Apple Neural Engine, GPU) highly preferred.
Proficiency in mobile frameworks (Dart/Flutter, JavaScript/React Native, Swift, or Kotlin).
Familiarity with data annotation, augmentation, and model optimization.
Job Requirements:
Authorization to work within the United States.
A problem solver capable of working independently and researching deployment bugs.
Candidates must provide a portfolio or GitHub link demonstrating past projects where an object detection model was successfully
trained and deployed to production or an edge device (webcam, phone, Raspberry Pi, etc.)
Compensation & Hours:
Start Date: Available immediately.
Temporary Part-Time Contract or Paid Internship (estimated 4 to 8 weeks).
Hourly Wage: $30/hour.
Completion Bonus: A $2,500 bonus will be paid upon the successful delivery of the functional prototype.
Flexible schedule requiring approximately 10–15 hours/week, designed to fit around class schedules if applicable.
Location: Hybrid in the Greater Madison, WI area (requires partial on-site availability for co-working and testing).
Build a functional prototype of a mobile warehouse utility app designed to instantly count stacked warehouse supplies using on
device artificial intelligence.
Train a lightweight, commercially viable custom object detection model (using frameworks like YOLOv8, YOLOv11, YOLO-NAS, or
YOLOX) to recognize pallets, top frames, and layer pads across varying lighting conditions and angles.
Prepare and organize data by setting up a lightweight annotating workflow (e.g., Roboflow or CVAT) to label a dataset of 300–500
images of inventory.
Export and optimize the trained model (via CoreML or TensorFlow Lite) to ensure it can run locally and offline inside the mobile
application.
Build a simple, clean user interface (UI) that integrates the model to display real-time counting overlays and bounding boxes on a
live camera feed or uploaded photo.
Co-work directly with one of the company owners to develop, iterate, and test the prototype.
Skills and Knowledge preferred:
Solid foundations and strong skills in Python for training pipelines.
Experience with computer vision libraries (OpenCV, PyTorch, or TensorFlow) and 1+ years of experience working with the YOLO
architecture.
Proven experience embedding machine learning models onto edge devices, with knowledge of leveraging hardware acceleration
(Apple Neural Engine, GPU) highly preferred.
Proficiency in mobile frameworks (Dart/Flutter, JavaScript/React Native, Swift, or Kotlin).
Familiarity with data annotation, augmentation, and model optimization.
Job Requirements:
Authorization to work within the United States.
A problem solver capable of working independently and researching deployment bugs.
Candidates must provide a portfolio or GitHub link demonstrating past projects where an object detection model was successfully
trained and deployed to production or an edge device (webcam, phone, Raspberry Pi, etc.)
Compensation & Hours:
Start Date: Available immediately.
Temporary Part-Time Contract or Paid Internship (estimated 4 to 8 weeks).
Hourly Wage: $30/hour.
Completion Bonus: A $2,500 bonus will be paid upon the successful delivery of the functional prototype.
Flexible schedule requiring approximately 10–15 hours/week, designed to fit around class schedules if applicable.
Location: Hybrid in the Greater Madison, WI area (requires partial on-site availability for co-working and testing).
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Job Location
Fort Atkinson, Wisconsin, 53538, United States
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