I honestly think if you are already a software engineer and you want to get into a ML company you should focus on building infrastructure for big ML products.

I honestly think if you are already a software engineer and you want to get into a ML company you should focus on building infrastructure for big ML products. It seems the infrastructure game is very new for realistic, production ready, machine learning. I mean Uber was the first to really describe the idea of having a feature store back in 2017 with their Michelangelo[0] framework. We are just now starting to see feature stores pop up as a SAAS model (Hopworks, Google's feast, etc.) I think we'll see "Machine Learning Engineers" start to pop up like crazy the next 2-3 years as people with a mixture of data engineering, machine learning, and software engineering experience begin to take these infrastructure roles. [0] - https://eng.uber.com/michelangelo/ https://eng.uber.com/michelangelo/