Hey, you might want to consider bert-as-service[0] for deep feature extraction from a BERT model. It will give you a 768 dimensional representation of the description, then you can embed that in the 512-dim latent space? I've been thinking of something similar.

It's not that hard to do it yourself, but it's a really clean package, and it gives you nice CLI flags for most things like pooling strategy, and what layer you want to get the activations from.

[0] https://github.com/hanxiao/bert-as-service