It fits quite well. In particular, many of our formalisms are used (if altered) all over machine learning. Having training as a physicist gives you a wide range of analytical skills.
I’ve seen former physicists doing everything from clinical pediatric cancer or bioinformatics to do chip design, financial work, and ML.
I cringed a little at "many of our formalisms". The maths of thermodynamics is so useful yet it took and takes substantial effort to pry the useful maths away from the thermodynamics gobbledigook that surrounds it.
But it's certainly true that Deep Learning with its combination of mathy underpinnings and poorly understood behaviour is something that fits very well with a physicist's skillset.
