Systems Engineering in Machine Learning - Navigating Low-Level Challenges
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Dive into a 48-minute podcast episode featuring Andrew Dye, a systems engineer navigating the world of machine learning. Explore the intersection of low-level engineering and MLOps as Andrew shares insights from his experience as a tech lead for ML Infrastructure at Meta and his current role as a software engineer at Union. Learn about distributed training, managing large-scale ML systems, and bridging the gap between firmware and MLOps. Discover how different engineering disciplines can work together effectively in MLOps teams, and gain valuable perspectives on the future of ML infrastructure and tooling. Hear discussions on topics such as execution patterns, rapid change adoption, consensus challenges, and the importance of abstractions in ML engineering.