That's not been my experience much at all work or research wise. Tensorflow, pytorch, jax are still very dominant. I've worked at several companies and interviewed at several dozen for ML roles. They have 100% been python/c++ for ml. I'd be impressed if even 2% of ML engineers used Julia.

I wanted to use Julia for some experiments but it's so confusing. I would call a function with VSCode and get "potential function call error" or something, with no details. Is it valid or not?

Also, I hate the idea of re-building all the code when the program starts. Python's JIT can at least ignore the performance-critical code that's written in C++.