Data Scientist

<h3>📋 Description</h3> • 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 <h3>🎯 Requirements</h3> • PhD or Master’s degree in Machine Learning, Computer Vision, Signal Processing, or a closely related field • 7+ years of experience building and deploying machine learning systems, with a focus on multi-modal or sensor fusion applications • Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow • Demonstrated experience working with camera imagery, RF signals and/or acoustic data • Deep understanding of signal alignment, temporal/spatial synchronization, and feature extraction across diverse data types • Proven ability to bridge research and application—delivering high-performance models in production contexts • Excellent communication and collaboration skills in cross-functional, interdisciplinary teams • Experience in maritime, aerospace, or other sensor-rich environments is a significant plus <h3>🏖️ Benefits</h3> • Competitive salary • Flexible work hours and the option for remote work. • Opportunities for professional development and continued education.