Most of the ML useful in industry is getting commoditized at a fast pace, and not enough people understand that. The focus on modeling for applying ML in a business environment is as incongruous as people believing programming is graph algo and compiler techniques. It sometimes is, but rarely.

It is much easier to learn the basics of ML if you have good software engineering skills than the opposite in my experience. The one thing that needs time learning is experimental design and quantitative analysis, and this is rarely taught well at university before PhD.