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, YOLONAS, 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 300500 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 realtime counting overlays and bounding boxes on a live camera feed or uploaded photo.
• Cowork 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 PartTime 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 1015 hours/week, designed to fit around class schedules if applicable.
• Location: Hybrid in the Greater Madison, WI area (requires partial onsite availability for coworking and testing).

About CTPS / Complete TransPack Solutions

Complete TransPack Solutions (CTPS) was founded in early 2017 to deliver on a single goal - improve the returnable & reusable packaging material asset supply chain by providing transparent and economically sustainable services to our customers. To accomplish our goal, we assembled a team of professionals that have individually devoted the majority of their careers to managing large-scale packaging materials pools and programs to support rigid container manufacturing. Our Mission is to provide transport packaging material services and solutions supported by our commitments for continuous improvement, food safety and efficient processes to consistently exceed our customers' expectations