Computer Vision Engineer Needed to Train a YOLO Model

We need a Computer Vision Engineer to train a YOLO-based object detection model on our custom image dataset. The goal is a working, accurate model that we can integrate into our pipeline for real-world use. We already have images. We need someone who can take it from annotation to a trained, evaluated, and exportable model. What the project covers: Review and validate our existing image dataset Annotate or verify annotations (YOLO format) Train YOLO model (v8 or v9 preferred) on our custom dataset Evaluate model performance (mAP, precision, recall) Fine-tune for accuracy on our specific object classes Export trained model in usable format (ONNX or PyTorch) Brief report on model performance and recommendations You are the right fit if you have: Proven experience training YOLO models on custom datasets Strong understanding of object detection metrics and fine-tuning Experience with PyTorch and OpenCV Ability to deliver clean, documented output Deliverables: Trained YOLO model file (exportable) Evaluation report with accuracy metrics Annotated dataset (if annotation is part of scope) Source code and training scripts Please share examples of previous Computer Vision or YOLO projects when applying. Generic proposals will be skipped.