Ab initio molecular dynamics (AIMD) simulations inherently incorporate many-body interactions and the coupling between intramolecular and intermolecular dynamics to the local environment based on quantum electronic structure calculations . However, simulating dielectric properties of liquid water using AIMD with sufficient time and length scales is challenging due to their slow convergence and collective behavior . Machine-learning force fields have emerged as a promising approach to produce ab initio-level potential energy surfaces .