A given nonlinear system can be represented via an immersion as rational or polynomial functions, thus leading to a simplified model structure. An immersion is a mapping of the initial state from the original state space to another state space, while exactly preserving the input-output map. In this note we show that the linearization of the system after immersion has an identical input-output map to the linearization of the original system before immersion. In other words, immersion and linearization commute. This is potentially useful for applications such as linear control design and sensitivity analysis after nonlinear identification, and has important implications for system approximation by linearization.