Machine Learning Engineer Co-Op
• Developed end-to-end development of real-time Computer Vision system using PyTorch and YOLOv8 for object detection,achieving 91% accuracy and 30% performance improvement through optimized image pre-processing pipeline• Implemented LOFTR matcher with PyTorch for damage tracking, utilizing Homography matrix for viewpoint invariance and achieving 91% accuracy through RANSAC-based outlier filtering• Fine-tuned YOLOv8 model on custom dataset of 5,000+ images using PyTorch, improving object detection performance by 40% through transfer learning and data augmentation tracking of pre-existing damages.• Established automated model monitoring using Weights & Biases and MLflow, reducing model error by 15% through systematic experimentation and achieving 91% precision in production