Explore the various structures of Machine Learning teams within organizations in this 23-minute video. Learn about the evolution of ML teams from nascent and ad-hoc setups to research and development-focused groups, business and product-embedded teams, independent units, and ML-first organizations. Discover the three broad categories of organizational design choices: the balance between software engineering and research, data ownership, and model ownership. Gain insights into how different company sizes and stages influence ML team structures, and understand the implications of centralized versus decentralized approaches to machine learning implementation.