I completely agree. Machine Learning is on the way to become a field like Web Development. There is a huge supply/demand gap that will only get wider.
(I'm guessing.)
In web dev, experimentation is cheap, so you make changes fast and see what happens. In many ML applications, trying stuff is expensive in time and/or money. So the best strategy is often to think hard about what could be going wrong, and make and test explicit hypotheses.
The difference definitely came as a surprise to me when I was making the transition.
For a long time as a non-web dev, I reckoned that I was smarter than 99% of the web devs. Then a web-dev friend of mine made his first few million $, and I reached some humbling conclusions.