In this paper, we explore the use of machine learning for multimedia indexing and retrieval involving single/multiple features. Indexing of large image collection has been well researched problem. However, machine learning for combination of features in image indexing and retrieval framework is not explored. In this context, the paper presents novel formulation of multiple kernel learning in hashing for multimedia indexing. The framework learns combination of multiple features/ modalities for defining composite document indices in genetic algorithm based framework. We have demonstrated the evaluation of framework on dataset of handwritten digit images. Subsequently, the utility of the framework is explored for development for multi-modal retrieval of document images. © 2013 Springer-Verlag.