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?
(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?