• Research, design, and implement advanced machine learning models that combine vision, RF, and acoustic signals for detection, classification, and tracking tasks • Architect sensor fusion pipelines that support robust, redundant, and context-aware perception in dynamic environments • Collaborate closely with domain experts and systems engineers to translate raw sensor data into actionable model inputs • Design and oversee data pipelines for multi-modal learning, including data alignment, augmentation, and pre-processing across modalities • Optimize models and inference workflows for low-latency execution on embedded and edge compute platforms • Lead performance analysis across individual and fused modalities, and drive strategies for improving robustness and generalization • Prototype and operationalize novel research in sensor fusion, uncertainty modeling, and representation learning • Contribute to long-term architectural decisions around multi-modal AI infrastructure, tooling, and evaluation frameworks • Document model design, training methodology, and validation processes with rigor and clarity.