Lessons Learned from MLOps for GenAI at Google Scale

The rise of Generative AI (GenAI) has revolutionized Machine Learning (ML) Development Workflows. Starting from large pre-trained models introduces new challenges in resource management, large model evaluation (both human and automated), efficient bulk inference, and effective handling of massive model embeddings. This talk distills key lessons and best practices from Google’s experience in deploying GenAI models at scale, focusing on the adaptation and evolution of MLOps principles to tackle the unique demands of this emerging field.