From my experience it is one of the most productive programming languages to develop in, and the code can be iterated on to reach performance that is as good as C or Fortran code.

Note that @krrutkow is the author so this answer is fairly definitive.

I cannot answer for the author, but for projects which build a lot of expensive numerical routines from scratch, Julia is a good fit: The JIT overhead is a small price compared to the high-level feel of the code and the resulting post-compiled speed.

This seems to be one of those “poster child” projects for Julia. As in there are likely lots of custom primitives or numerical routine that’d be impossible to have perform well in Python/Numpy but still saving development effort over coding a custom C++ case (much less C++ expertise needed to do so).