This blog post presents the development of Pinterest's large-scale learned retrieval system, emphasizing its two-tower model architecture for candidate generation and ranking from user engagement events. It discusses techniques for efficient retrieval in a production environment, including auto-retraining and version synchronization to maintain model accuracy. The authors detail the challenges and results from implementing this system to enhance user engagement across Pinterest's platform.