As far I expierenced it, it gets really boring at some point, because some predictions feeling kinda useless. Or you need a f-load of parameters to produce an "okay" result. And at some point, you wish you could debug a trained model.

Most bosses or companies don't know, what ML is really doing. They believe we can put some random data inside the model and after that, the output gonna be a gamechanger.

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I'm doing a lot of automation and optimizing processes. My first boss wanted, to implement "some AI" in our process. I told him, it makes no sense to train a model, if our process is already stright forward and deterministic.

He wanted it anways, so I added a portion sarcasm to it: "Maybe in a private Blockchain with Kubernetes?"
He was all in.

So I guitted this job after a few months.

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But here's my opinion/suggestion:

If you love working as ML-engineer -> go for it. It's still hypetech and companies throwing money at it. (Till the next "AI" winter)

But learn some programming skills for being a developer at one day -> developers are higly needed! And this won't change over the next decades.