Do bindings like this help much with the day to day work of machine learning research? Are the kinds of errors you encounter the kind that could be avoided with a smarter type checker?
Although this is somewhat of an extreme example, I'd say most of my tensorflow models take at least several minutes to build a graph. Anything that reduces the possibility of runtime errors would therefore speed up my development cycle dramatically. I'll also note that the OCaml compiler is lightning-fast compared to say, gcc.
What are you doing that requires a 10, 30, 45 min graph build?
In fact I'd wager your average Haskell type error has generated more than a few frustrated stackoverflow questions.
I'll say however, the benefit of an ML like Ocaml is less so the types than that functional languages are the most advanced in providing tools which allow for domain modeling in terms of composition and defining tailored algebras. This is something that fits both applied and experimental machine learning especially well.
If you look at the issues, you'll see the developer contemplating GADTs to deal with tensor shape matching (but even phantom types will do). This is an issue that causes headaches for just about anyone whose dealt with neural nets.