Contour eigensolvers, such as FEAST and Beyn’s method, are a popular class of algorithms to solve univariate eigenvalue problems. These methods enable the solution of eigenvalue problems that are too large for standard QR/QZ based eigensolvers. In addition, the vast majority of the computational work is embarrassingly parallel, a property not shared by standard solvers. I will discuss a generalization of contour eigensolvers that can be used to solve multiparameter eigenvalue problems. As in the univariate case, the vast majority of the work is embarrassingly parallel, and the method allows us to approach eigenvalue problems that are too large for the standard approach. I will also give a few applications of this method.