I can tell you first hand that the money at MIT is not going to Julia. Okay, there was a few years we had a devops person dedicated to making the JuliaLang organization work (at probably half the salary of FAANG for the love of OSS and MIT prestige), but the vast majority of the money does not go to Julia. For grant money at MIT, more than 50% is siphoned away before it gets to the lab. Then, the vast majority of that leftover money is not for software development but instead for research in methods for parallel computing, scientific machine learning, and applications to XYZ (you can just take a look at my CV or Alan Edelman's if you're curious about what the Julia Lab actually does).
While a lot of this research does trickle back into the Julia ecosystem, it's much less direct than Facebook paying the day salary for a bunch of PyTorch engineers. In fact, it's almost the opposite: most of the people who are paid are graduate students, who may be at risk of graduating if all they do is contribute to Julia instead of getting the required research manuscripts written.
One of the major transformations that has happened to the ecosystem though is that post-1.0 it has gotten some pretty wide industry adoption, along with some major success stories built directly off of the Julia ecosystem. Julia Computing, Pumas-AI, RelationalAI, Invenia, and Beacon Biosystems are just a few companies that are noteworthy of hiring a good number of contributors to the language and package ecosystem. The hiring by these kinds of entities has actually been growing so rapidly that it's a great labor market to be looking for a job in. But most of this hiring frenzy is not driven by MIT.