I was in a combo program, got my Master's in ML on the way to a PhD. I really didn't quite understand academia before I entered. It got to the point where I cou

I was in a combo program, got my Master's in ML on the way to a PhD. I really didn't quite understand academia before I entered. It got to the point where I couldn't see the light at the end of the tunnel, I had spent 4 years on a very long paper that didn't represent my own desired direction of work in the field. And the whole time I had simmering thoughts that I'd rather being building software in an engineering context, that academia was not my place. I eventually quit and did find a job with a smaller company building math-heavy analysis software for an engineering field. I'm quite happy with my choice; I pick my language and tools, I have complete agency over my part of the product stack, and I solve interesting problems. Sometimes I entertain the "what-if," but I see the ML industry as stuck in a massive bull-trap bubble, with a lot of people working on "products" that add zero value to their company's portfolio. I don't chase easy money, I chase interesting work.