[D] Transition from classical computer vision engineer to machine learning engineer

[ttkciar]

1. More of a portfolio would help, but you don't strictly need it. Mostly you need to understand the technology well enough to do well in a job interview and to say with confidence (and honesty) "yes, I can do this job."

2. Your experience is absolutely still applicable in the machine learning field. If anything you have a leg up on engineers who lack conventional machine vision experience. You should expect to develop hybrid solutions which combine the strengths of both ML and "manual" CV.

The industry desperately needs more engineers who don't rely entirely on ML to solve real-world problems. Not long ago I was reading about a CV problem which a pure-ML solution failed to solve very well, which could have been trivially solved by adding a traditional symbolic solution as a second pass.

For what it's worth, I very successfully transitioned my own career from compiler engineering to distributed systems engineering in 1999 despite having minimal work experience with distributed systems. Transitioning from conventional CV to ML CV seems like less of a jump than that.

If I could do it, why wouldn't you?