Recently, I’ve been working on the reproducibility of machine learning research. In practice, this meant doing far more infrastructure work than actual machine learning modeling. I found myself digging into operating systems, containers, storage, and hardware details. and suddenly, I started questioning everything, not because it wasn’t interesting, but because I was drifting away from the kind of problems that originally made me fall in love with machine learning.