[alexbeloi]

You might want to look at "Machine Learning Engineer" positions if you want to do ML in practice, it's starting to be a title I see somewhat often now.

As others have pointed out Data Engineering is more about building data pipelines, making architecture decisions for your ML stack, things like that. Less about model building, prototyping and training, which is what I think of when somebody says they 'do' ML.

[mattnewton]

Right, I'm not picky about the title. I'm looking at those positions too. The main thing is, I want to be able to contribute using my existing software engineering skills from day 1, while picking up the ML stuff. It's been really hard to basically work an unrelated job during the day and go home and do kaggles for practice, so I am hoping to get more of an intersection as a launching place. Anything touching the data or the models will do :)