I have a fleet of miniskid machines collecting image, sensor, and GPS data while they work around the ranch. I want a functional AI model that lets these machines handle two specific chores on their own—feeding animals and mucking stalls. Here’s what I need from you: • Build and train a computer-vision / sensor-fusion model using the data I’ll supply. • Tune the model so the miniskids can operate autonomously, recognizing feed locations, stall layouts, obstacles, and task completion states. • Package the trained weights, inference script, and a concise README covering setup, required libraries, and how to deploy on the existing machine controller. • Provide a short test plan I can run in the field to confirm the model consistently performs both chores without human intervention. A clean, well-commented codebase (Python preferred) and clear documentation are essential. If you have experience with edge‐deployment on NVIDIA Jetson or similar platforms, highlight it—that’s the environment on most of our units. Looking forward to seeing how you can turn raw ranch data into truly hands-free chores.