> It's similar to data engineers thinking they will do real ML some day and their data job is just temporary...
Hah yeah but this is just the reality of ML. "Engineer who only codes up awesome new ML algorithms" isn't a real job. For every 1 person coming up with exciting new algorithms, there's 500 people dealing with data pipelines, cleaning, maintenance, and operations. A while ago I got hired by a large SF tech company as a "machine learning engineer" and my team spent nearly all of their time writing Javascript web wrappers on top of scikitlearn. Thrilling stuff.
Hah yeah but this is just the reality of ML. "Engineer who only codes up awesome new ML algorithms" isn't a real job. For every 1 person coming up with exciting new algorithms, there's 500 people dealing with data pipelines, cleaning, maintenance, and operations. A while ago I got hired by a large SF tech company as a "machine learning engineer" and my team spent nearly all of their time writing Javascript web wrappers on top of scikitlearn. Thrilling stuff.