I can confirm. We regularly look for people to write some computational physics code, and recently for people using ML to solve solid state physics problems. It’s way easier to bring a good physicist or chemist to a decent CS level (either ML or HPC) than the other way around.
You can teach a mathematician what he needs to know about finance, you can hardly do the opposite.
Neither the Physics nor the CS are cutting edge (that’s why we do not necessarily reject people with limited experience in Physics, though they need to show motivation and abilities to learn); what is is the combination of both.
We’d like to be as close to the cutting edge on ML as possible, though, because it’s a significant competitive advantage to be able to use fancy new techniques before our friendly competitors. But as I said it seems to be easier to train a Physics or Chemistry undergrad to get some feeling about how ML works than to train a CS undergrad to have some intuition about the Physics. And intuition is critical to detect when models hallucinate and get off the rails.