I mean the main answer is familiarity and the abundance of code available in Python.

Some people are exploring alternate routes. You can use the PyTorch C++ API. Meta released Flashlight. Both Rust and Go are picking up in ML (more Rust than Go, now, I think but Go has Gorgonia, for Rust there is a Torch interface https://towardsdatascience.com/machine-learning-and-rust-part-4-neural-networks-in-torch-85ee623f87a)

But often you start going down these roads to later find that they're not worth it. Much of the computational savings can be done without forcing a new language on people. The whole "shaping your thinking around the framework" is an unfortunate necessary evil because of the nature of how the networks are used (via high speed devices like GPUs/TPUs) or how data gets assembled or transferred. Sadly, a lot of this is not the fault of the top-level language.