Is it a natural design pattern to use closures and dynamically defined functions in Python?

I find that defining functions which ask the user to define and then pass in another function to be a very natural design pattern for me. For example,

def gradient_descent(x0, grad_f):
    x = x0
    for _ in range(100):
        x -= 0.1 * grad_f(x)
    return x

Implements a generic gradient descent routine; all the user has to do is define the gradient function for f. This is basically the interface used by scipy.optimize, and the programs I write tend to use various function closures and dynamically defined functions in a similar way.

However, I have found myself facing some serious difficulties in taking advantage of parallelism with multiprocessing since functions can't be pickled. I know that there are ways around this, but it makes me question whether programming like this is even a "pythonic" way to do things.

Is this a natural design pattern in Python? Is there a better way to design programs that will likely need to be refactored to use multiple processes?