Get a PhD in ML from a top school. If you can't, get a MS CS/DS with ML emphasis from a top school, AI grad cert from Stanford at a minimum so that you can understand the latest arxiv papers. If you can't, YOLO and sift through a lot of low-quality articles on the Internet, find the gold nuggets and learn to apply them rapidly and then hope somebody will notice you and hire you. Competition is brutal right now as AI is the only area that is still hiring like crazy. I still think you are 5-10 years too late to start right now. If you can do DevOps, you can likely learn MLOps quickly but it's the same horrible job as regular DevOps. Also, data engineering is not ML but those jobs are easier to find.
EDIT: For downvoters, that's how I did it. I was a very successful SWEng (some of my work was among top posts on HN under different nicks) but saw the ball rolling towards ML in 2012 so I reskilled.
EDIT: For downvoters, that's how I did it. I was a very successful SWEng (some of my work was among top posts on HN under different nicks) but saw the ball rolling towards ML in 2012 so I reskilled.