In this example, we show how ML optimizers can be conveniently utilized in developing complicated physics-driven force fields, using DMFF. This is a relatively straightforward way to take the advantage of an automatic differentiable force field calculator. Meanwhile, the reweighting MBAR estimator implemented in DMFF makes it an even more powerful tool in top-down parameter optimization, as we will show in the next two sections.