Word Embedding using transformers (BERT, Roberta, or any other model) or Fast-text, Glove etc?

I am training a model to learn title similarities between two titles. I have around 2-3 Million lines of text data, scraped from multiple sources. Now I want to use that data to train a model that can learn title similarity. For example Finance officer is close to the Finance lead compared to the sales officer.

Which models should I go to? Fast text, Glove, or transformer-based models.
Note: at inference time I will give titles only and compute some similarity metrics like cosine distance or something else.