We’ll explore strategies for optimizing machine learning workflows to drive faster innovation and improved productivity. We’ll discuss key challenges in ML development, including latency, measurability, and deployment speed, and share insights on how to overcome them. By leveraging best practices, such as AB testing, streamlined data landing, and efficient feature engineering, teams can significantly boost their ML throughput and efficiency, ultimately driving business growth and success.

Sonam has over 20+ years of experience spanning tech startups, Microsoft, Google and Meta Platforms (previously Facebook) and has spent the last 13 years building large scale AI systems. He is part of the Applied AI team at Meta and currently leads Meta’s Monetization ML Infra team.