Ask HN: How to pivot to a Machine Learning engineer?

Software engineer here with 10+ YOE building data (mildly) intensive applications: mainly back-end development experience (from legacy to modern/cloud-native applications, brownfields and greenfields).

(1) is it wise to do this transition?

(2) has anyone else here in HN done it?

(3) how can I do it if my job has no ML in it?

Is there an ML engineering practice that isn't focused on building models but more on managing/deploying/scaling models? i.e. can I avoid learning all the maths underneath?