Intern - Metro

The Automated Defect Classification 2.0 project focuses on improving defect detection accuracy across multiple inspection platforms like ATI Wind and Dragonfly. The role involves training advanced machine learning models, validating their performance, and integrating them seamlessly into the production line to reduce human error. Key tasks include analyzing defect data, optimizing models based on feedback, and providing training to team members on model usage.