Much like Software Engineering followed Computer Science, as our world increasingly depends on machine learning systems, we argue that the time is right for ML Engineering to come of age. Our paper on ML Engineering is now available on arXiv. It covers a decade of production ML experience, illustrated by two successive end-to-end (E2E) ML platforms at Alphabet: Sibyl and TensorFlow Extended (TFX). I hope you will find it useful and that sharing our experience will help you advance your own ML systems.
Humbled to have played a small part in advancing both of these platforms working together with Konstantinos (Gus) Katsiapis, Abhijit Karmarkar, Ahmet Altay, Aleksandr Zaks, Alkis Polyzotis, Anusha Ramesh, Ben Mathes, Gautam Vasudevan, Irene Giannoumis, Jiri Simsa, Justin Hong, Mitch Trott, Noé Lutz, Pavel Dournov, Robert Crowe, Sarah Sirajuddin, Tris Warkentin, Zhitao Li and many other current and former Googlers acknowledged in this article.
I joined Google on May 10th, 2010 and got this plaque to commemorate my 10th anniversary.
10 Years at Google
The company has grown and changed a lot over the years. In some ways I feel that Google is a different company every year. Always evolving rapidly, every system continuously improving or … deprecated and rewritten.
At the same time the core has remained constant. The bottom-up nature of innovation while frustrating (“why can’t we simply ask the VP to mandate X?”) is extremely empowering. The values still strong: while the company does stumble occasionally (we are not perfect), I strongly believe it is fundamentally a force of good in the world which is very important to me personally and makes me proud to be here. I agree with Peter Drucker (thank you Carnegie Mellon University Silicon Valley for introducing me to his writings): businesses need to deliver way more than return on investment, and Google always strives to do that.
Most importantly, the people I had the privilege to work with at YouTube, Google Search and now Google AI / Google Research have been inspirational and continue to reinforce my impostor syndrome daily 🙂 Same applies to Google partners and external collaborators I met along the way: you have helped me grow for which I am grateful. I hope that together we will overcome these uncertain times.
After 5+ years working on Developer Relations @ Google I decided to go back to product development and joined the Research & Machine Intelligence team at Google as the Technical Program Manager. I’m working on machine learning (ML) infrastructure and large scale ML deployments, and could not be more excited about this next logical step of my journey.
Fun fact: my Computer Science undergrad degree was in AI, and I did neural network work during my graduate studies, but it took me a few years to get back into it. Those dang AI winters got in the way. Timing is everything.
More updates soon, in the meantime check out TensorFlow.org!