Communication is critical to the scalable and efficient performance of scientific simulations on extreme scale computing systems. Part of the promise of task-based programming models is that they can naturally overlap communication with computation and exploit locality between tasks. Copy-based semantics using eager communication protocols easily enable such asynchrony by alleviating the responsibility of buffer management from the user, both on the sender and the receiver. However, these semantics increase memory allocations and copies and in turn affect application memory footprint and performance, especially with large message buffers. In this work we describe how the so-called "zero copy'' messaging semantics can be supported in Converse, the message-driven parallel programming framework that is used by Charm++, by implementing support for user-owned buffer transfers in its lower level runtime system, LRTS. These semantics work on user-provided buffers and do not semantically require copies by either the user or the runtime system. We motivate our work by reviewing the existing messaging model in Converse/Charm++, identify its semantic shortcomings, and define new LRTS and Converse APIs to support zero copy communication based on RDMA capabilities. We demonstrate the utility of our new communication interfaces with benchmarks written in Converse. The result is up to 91% of message latency improvement and improved memory usage. These advances will enable future work on user-facing APIs in Charm++.