I have had a similar experience, but I really do think it points more to the team than it does to the efficacy of machine learning. I was on a team of extremely intelligent people, but they were very academic, with minimal practical coding skills, refusals to use version control etc. By academic, I mean graduates from the number one university in their respective fields, top publications, etc. They produced very little actual value. Great theoretical ideas, in depth understanding of different methods of optimization, etc.

The team I was on before that one was a bunch of scrappy engineers from Poland, India and the USA with no graduate degrees, but 20 years coding and distributed systems experience each. The difference in problem solving ability, the speed at which they moved, broke down problems, tried out different methods, was staggering.

I think ML is suffering from a prestige problem, and many companies are suffering for it. The wrong people are being hired and promoted, with business leaders calling the shots on who runs machine learning projects without fully understanding who can actually deliver.