My professional interest is the intersection of machine learning and engineering management. I’ve been an ML engineer, manager, and manager-of-managers at a variety of different stages in the company lifecycle. Most recently, I led Stripe’s machine learning infrastructure group.

Why ML + EM?

I’ve always been interested in pushing the boundary of what’s possible with ML and AI. Specifically, I’ve been motivated by the real-world applications of these new technologies – how can we turn these brand new capabilities into something that makes a difference, and actually makes our lives better?

In my early career, I was fortunate to be a part of some high-functioning engineering teams that consistently delivered on very hard problems. And I also have been a part of engineering teams which struggled to achieve results despite having truly talented engineers. I’ve come to believe that a core piece of the puzzle is engineering management, and I’ve spent a lot of my career trying to understand exactly what good engineering management is.

I think that building great machine learning teams is mostly the same as building great software engineering teams. But there are a few things which are even more important (and maybe a few which are less important). I’m still trying to learn and grow as an engineering leader, and my goal is to use this space to share what I’ve found and reflect on my journey.