What's it like being a Machine Learning engineer, really? I understand you're doing a lot of 'data pipelining', but how much building are you actually doing? Ever since I've started programming I've thought of over 25 projects to build... but only a subset feature ML concepts. I'd want to be able to program/build extensively but not exclusively using ML - am I better off being a SWE? PS: Currently in an MSCS, very ML-heavy.
I'd also appreciate resources/links to help guide me/understand the role a bit better.