[probably_wrong]

Maybe it's an instance of "when all you have is a hammer...", because I'm learning about it right now, but you could look into transfer learning - you train a ML model in a similar, easier task, and then you tweak it with your data.

That said, there's a good chance that your current algorithm is all you will ever need - many times a ML project is too much, and you already have good results.

[minimaxir]

Transfer learning only works if the original model is in the same domain (e.g. ImageNet for images, GloVe for text). A bespoke problem likely won't have a widely-available original model.