Only a very small subset of industry cares about academic publishing, and even within that subset it's only a fraction of groups at a fraction of corps that consider publishing a primary or even secondary objective.
The groups that do care about those things can be good gigs, but are generally not the place in the company you want to be anyways, unless you can get in and out (for good) in <10 years. If you can do something that actually impacts the business -- that is actually useful to other humans -- no one gives a shit about h-indices or kaggle scores. And you'll be better compensated anyways.
> can do something that actually impacts the business -- that is actually useful to other humans
Do not confuse these two. That's incredibly naive.
Read more pure math papers, then you will see the difference. :-)
This is no contradiction: there exist quite pure math papers whose content is very relevant for the mathematics behand ML algorithms. :-)
I do have the impression that the kind of research in ML that is not strongly associated with the recent "machine-learning industrial complex" by now tends to become published in another subject area.