We present a new parallel implementation of lazy ML. Our scheme is a direct extension of the G-machine-based implementation of lazy ML. Parallelism is introduced by fork annotations inserted by the programmer. We discuss the interference of such user annotations with strictness annotations generated by our compiler. The system has been implemented on a Sequent Balance computer. We also address the main practical issues involved, including stack and heap management.