I‘d argue that integrating ML into a project isn‘t the hard problem, as it was described in this article. Most people will, after some research, be able to build some basic ML functionality using popular libraries and a bit of python. The hard thing about ML is, when you try to actually understand it. I‘ve met many „ML engineers“ who do their job but do not actually understand what they‘re doing. Understanding ML doesn‘t have to do a lot with coding. It‘s math and statistics.