1) There's a kind of "hard" learning you're learning a fixed, structured way from a textbook.
2) There's a kind of "soft" learning which is transmission of knowledge, which happens a lot more face to face when you're working together.
3) Then there's a kind of research learning, where you're doing something new, usually with collaborators.
The second and third are really best done in certain environments like research or good companies
Furthermore, do not underestimate the importance of sheer luck. Exaggerating a bit, deep learning was just another subfield of ML, until GPU-powered DL really took off and made the researches behind the most fundamental ideas superstars. This is not a given, and it might take years or decades until it's really clear whether you're making an impact or not.
I wish you the best of luck, InkCanon, and stay excited!