Employment density maps, which are key to targeting urban investments, are often outdated, imprecise, or unavailable. This note demonstrates a machine learning approach for high-resolution urban employment prediction that can open new avenues in developing countries for targeted urban investment and planning decisions that are based on systematic empirical evidence.