Etsy prioritizes safety and trust in its marketplace to empower creative entrepreneurs. With over 100 million unique items and 7 million active sellers, Etsy employs a Trust & Safety team dedicated to enforcing policies and removing potentially violating content. To enhance detection capabilities, Etsy utilizes Machine Learning, including supervised learning models, leveraging multimodal signals (textual and imagery) from listings. The model architecture includes text and image encoders to learn representations and employs a neutral class for non-violating listings. To address data imbalance, focal loss is used. Model evaluation involves offline training and production deployment through A/B testing. Etsy continuously iterates and improves its detection system by deploying promising offline candidates and monitoring performance. As a result, over 100,000 violations have been identified and removed, supplementing other detection methods. Etsy remains committed to using innovative approaches, including Large Language Models, to enhance its safety measures.