From your comments I gather numerical algorithms aren't really your area. It really has worked as a separate silo for decades, and experts probably have little interest in ever writing a web server. What is the problems you are referring to? Aren't there also going to be problems with using one language for everyone (like array indexing headaches for starters).
I think Julia is older than numba by the way. Personally I haven't used it much, but I like the idea.
I gather from these comments that Julia is not a good choice for run-of-the-mill devs that do numerical computation on the side, but might be ideal for someone who's entire job is to write algorithms from scratch. Correct?
I'd say it's not a good choice if like your example, you want to integrate with a mature web framework, or something else that only Python has (though Julia FFI allows to call Python almost like you're writing python directly in the Julia code), or if you already have an infrastructure in Python.
For run-of-the-mill numerical computation, like you said it's good writing loops and code that is really natural and run it fast. Most commonly used algorithms for data science and scientific computing are already written in Julia, you don't need to write them from scratch. But it's good to have libraries that you can easily inspect, understand and extend within your code.
I think Julia is older than numba by the way. Personally I haven't used it much, but I like the idea.