1. There is much more supply than demand in terms of Machine Learning and Data Science. There aren't actually that many jobs outside of research, it's just that the hype makes it look that way. Now that all these PhDs seem to be starting in ML, I wonder what they will do in 4-5 years when they finish the degree. I don't think a market for them will exist.
2. Many companies don't know what they are doing. They are hiring ML people because they want to put AI into their marketing materials. In reality, they don't need ML, they just need someone collecting data, building a database, and running a query. They just don't realize that's the case. The same happened with "Data Science" and "Big Data" - What most companies needed were software engineers building infrastructure and data collection, not people running sklearn.
Somebody should start a thread that captures the silly examples of this. My personal favorite was a workout template “powered by AI”. Mind you, the only information the customer provided was the basics like age, sex, weight, and goal. This signaled peak AI hype for me.
That’s one way of looking at it. Perhaps another way is ask why all of these employers are hiring people who have done low quality research without understanding who they’re really hiring.
It reminds me of the adverse market effects on gamers when Bitcoin miners were buying up all the GPUs a few years ago. It’s another emergent collective phenomenon that’s distorting the market.
I think there may be quite a few employers out there with non-technical management who have become convinced that they need to hire a machine learning expert, without any particular reason why. They might hear a competitor has hired someone and so they need to as well. Really weird.