Custom Video AI Model Training

I’m looking to hand off the full training cycle of a video-based AI model that fits a rather niche use case. The footage you’ll receive doesn’t fall into the usual sports, surveillance, or educational buckets, and the end-goal goes beyond typical object detection, action recognition, or basic content moderation. We have a very particular outcome in mind that we can explain once an NDA is in place; think of it as a hybrid of fine-grained scene understanding and domain-specific tagging. The raw videos arrive in a mix of proprietary and uncommon container formats. You are free to convert or transcode them however you like as long as no perceptual quality is lost. We’re flexible on frameworks—PyTorch, TensorFlow, or a well-maintained alternative—but the final model must be exportable to ONNX or TensorFlow SavedModel so our engineers can integrate it into an existing inference pipeline. Deliverables • A fully trained model that meets the accuracy benchmarks we’ll define together (precision/recall on a held-out test set). • Reproducible training code, including data loaders, augmentation steps, and environment configuration. • A short README detailing setup, hyperparameters, and the exact commands to reproduce results. • One live hand-off session or recorded walkthrough to ensure we can fine-tune the model internally later. I’ll supply the videos, and a labeling guide. You bring expertise in video preprocessing, GPU-accelerated training, and model optimization for real-time inference. If this kind of custom challenge sounds interesting, let’s discuss next steps and define milestones.

Project ID: 39739094