What kind of library stack do you use? Julia has lots of interesting niche libraries for online inference, e.g. Gen.jl, which can be quite relevant for a hedge fund.
If you can't talk about library stacks, it'd be at least interesting to hear your thoughts about how you minimize memory allocation.
Very little actually, we try to minimize dependencies, especially for the core inference engine. We just have some basic stuff like Statistics and LinearAlgebra. We use a lot more libraries for offline analysis, but even there it's just popular stuff like DataFrames combined with our own code.
We control memory allocation the boring, manual way – we preallocate all our arrays, and then just modify them, so that we have very little continued allocation in production.