A new framework called MaRK is introduced for dynamic operator conditioning in State Space Models (SSMs) for sequence modeling. It allows for context-indexed parameter modulation, enabling adaptive temporal dynamics. The authors demonstrate the effectiveness of MaRK on a frozen SSM backbone, achieving low trainable parameter counts and stable memory profiles.