This paper introduces a novel hardware-aware Neural Architecture Search (NAS) framework that integrates deployment-aligned low-precision training. This approach addresses the accuracy degradation caused by the mismatch between full-precision optimization and low-precision deployment on edge accelerators, particularly for spaceborne AI applications.