Coming from the excellent tidyverse or even data.table in R, Numpy always has felt like twenty steps back into mindfuck territory.
Numpy and tidyverse/data.table are not really on the same level of abstraction. Something like Pandas would be (and it definitely has its warts).
Doing the lower level stuff that NumPy is used for is really mindfuck territory in R.
There's also the fantastic "tidytable" library. I wouldn't want to implement multi-headed self attention in either of those libraries though.
I've done only very simple ML stuff using R and it never feels like exactly the right tool.
I had to write a normal codebase in R exactly one time and it was one of the weirdest and most unpleasant coding experiences I've had. After that, I decided R is tidyverse and a handful of stats libraries. If you need more, reach for another tool.
I never understood the appeal of tidyverse. I have a colleague who, like you, thinks that R is tidyverse. He also has the nasty habit of starting Excel formulas with a '+' sign.
The main attraction of tidyverse is that it's easy to copy-paste code for common cases. If there's no ready recipe for something, it's usually just not done, or some "technical person" is called to do it.
R is used mostly as a fancy calculator, which is fine in itself, but it makes the comparisons to general purpose languages like Python quite apples-to-oranges.