The engineer will contribute across the full algorithm lifecycle, from first-principles formulation and high-fidelity modeling through software integration, calibration, field demonstration, and validation, and will collaborate closely with Business Development, Production, and cross-functional Engineering teams. Apply statistical signal detection frameworks, including Neyman-Pearson, Bayesian, and CFAR methodologies, to maximize probability of detection across varying noise, interference, and target conditions.