"An attempt to go hard on machine learning and apply it everywhere will probably work out pretty badly. I haven't the slightest idea what new and novel problem I'd solve with it that doesn't have a better solution through a more straight-forward approach."

Assuming they have the money, isn't this exactly the kind of reason Google should train up a wide spectrum of engineers from different teams and then see how they apply machine learning to their respective domains? It would be foolish for Google's management to think they can divine a priori all the best possible uses of ML in their various lines of business. Why not tool up a bunch of smart people, set them loose, and see what works?