I recently went through this and conda handled the python deps pretty well, but the nvidia cuda stuff was a massive pain to get the right things installed. I think it’s safe to blame nvidia.
It seems I may have stepped on a few toes here. For a lot of ML engineers I've talked to, conda is a living nightmare if one tries to go beyond one project (or maybe multienvironment) on one machine.
Sometimes even one is a problem.
I don't think I've talked to a career ML engineer yet that has had a positive work experience with conda, that I can recall. Usually the question has been a good way to trauma bond, which is always good.
It seems like this is more an academic kind of thing?