This paper examines the problem of estimating the parameters describing system models of quite general nonlinear and multi-variable form. The approach is a computational one in which quantities that are intractable to evaluate exactly are approximated by sample averages from randomized algorithms. The main contribution is to illustrate the viability and utility of this approach by examining how high computational loads can be simply managed using commodity hardware. The proposed algorithms and solution architectures are profiled on concrete examples.