I wanted this article to convince me, but they really don't acknowledge the reason that everyone currently uses Python - the libraries. Do linear algebra using lightly wrapped C? numpy. What about NLP? spaCy. Implicitly specify a computation graph with high level code? PyTorch. Explicitly specify a computation graph using leaky C++ abstractions? TensorFlow. And using either PyTorch or TensorFlow, you get to interact with CUDA.
For now, if you want a functional language for doing deep learning, IMO that language needs Python interoperability. Long-term, I'm hopeful that GraalVM [0] can provide a way of calling Python from the JVM, but until then, I think the best option is coconut-lang [1], "a functional programming language that compiles to Python." You get pattern-matching, TCO, the pipe operator, and ADTs, all while being one AOT compilation step away from Python.