I'm not sure what you're saying about DL in NLP is completely true. To train e.g. a language model from scratch you'll need a load of data, but building on top

I'm not sure what you're saying about DL in NLP is completely true. To train e.g. a language model from scratch you'll need a load of data, but building on top of pre-trained models (e.g. BERT, ELMo), or even just using pre-trained word embeddings in your RNN, reduces that a lot. Subsequently using these will require some knowledge of ML, even if just to know what the library code for some model you glue on does.