Synchrotron light source storage rings aim to maintain a continuous beam current without observable beam motion during injection. One element that paves the way to this target is the non-linear kicker (NLK). The field distribution it generates poses challenges for optimizing the topping-up operation. Within this study, a reinforcement learning agent was developed and trained to optimize the NLK operation parameters. We present the models employed, the optimization process, and the achieved results.