The design of binary error-correcting codes is a challenging optimization problem with several applications in telecommunications and storage, which has been addressed with metaheuristic techniques such as evolutionary algorithms. Still, all these efforts are focused on optimizing the minimum distance of unrestricted binary codes, i.e., with no constraints on their linearity, which is a desirable property for efficient implementations. In this paper, we present an Evolutionary Strategy (ES) algorithm that explores only the subset of linear codes of a fixed length and dimension. We represent the candidate solutions as binary matrices and devise variation operators that preserve their ranks. Our experiments show that up to length $n=14$, our ES always converges to an optimal solution with a full success rate, and the evolved codes are all inequivalent to the Best-Known Linear Code (BKLC) given by MAGMA. On the other hand, for larger lengths, both the success rate of the ES as well as the diversity of the codes start to drop, with the extreme case of $(16,8,5)$ codes which all turn out to be equivalent to MAGMA’s BKLC.