there's some calculus in ML like maybe Lagrange multipliers etc, basic stuff (ML can, however, go higher than calculus , like topology, geometry etc), but the money is in the tensorflow, scikitlearn, keras, etc, so while many algorithms use calculus for proofs / derivations, no one is paid to do that.
Either you're paid to be good at programming- aforementioned scikitlearn, pytorch stuff etc, or you're paid (as an academic) to research new algorithms, and the math used here can go way higher than calculus (usually does). But also, idk what heavy use means