Crankshaft dampers are a common approach for controlling engine crankshaft vibration. The optimum damper parameters are relatively easy to determine for the case of single-mode systems and multi-mode systems with a dominant mode, provided that the primary system is undamped and the system response is linear. For nonlinear systems such as internal combustion engines that experience complex periodic inputs, the true optimum damper parameters may not be apparent. The crank kinematics introduce nonlinear torques acting on the crankshaft. In addition, the gas torque is, in some sense, a state-dependent input, as it is a function of not only the energy addition per cycle, but also of the crank angle. It is reasonable to expect that truly optimal damper parameters may not be obtained using classical approaches. As an alternative, genetic algorithms may be used to determine optimum crankshaft damper settings for this complex system. This paper will present the modeling of an internal combustion engine from the perspective of determining crankshaft vibrations. Optimum damper settings are then determined using a genetic algorithm. Simulation results are shown that compare the achievable vibration reduction in an engine equipped with a GA-tuned damper and the reduction achieved with a conventional passive damper.