<h2><strong>Your next mission</strong></h2><p style="min-height:1.5em"><strong>Turn complex radar data into clear detections – so our software can spot birds, drones, and airborne threats in real time.</strong></p><p style="min-height:1.5em">As our Deep Learning Engineer, you architect and implement object detection frameworks for non-natural radar imagery. You work side-by-side with fellow AI specialists, software engineers, and radar experts to ensure your research translates directly to edge computing hardware. </p><p style="min-height:1.5em">Reporting to the AI Lead, your models directly power live radar systems across the globe.</p><h2><strong>What you'll do</strong></h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em"><strong>Framework design and architecture:</strong> Build robust detection, segmentation, and tracking models for complex 3D, 4D, and 5D radar data. Translate raw signal processing concepts into high-performing neural network architectures.</p></li><li><p style="min-height:1.5em"><strong>Data strategy and label management:</strong> Develop innovative strategies to handle imperfect, sparse, or missing radar labels. Automate dataset creation and labeling workflows to keep research moving fast.</p></li><li><p style="min-height:1.5em"><strong>Model optimization for the edge:</strong> Optimize neural networks using TensorRT for real-time, low-latency inference. Ensure every model runs smoothly on edge hardware deployed in the field.</p></li><li><p style="min-height:1.5em"><strong>Cross-functional integration:</strong> Partner closely with software and radar engineers to integrate your models into live products. Co-develop and refine deep learning approaches alongside your AI teammates.</p></li></ul><h2><strong>What you bring</strong></h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Master's degree in Computer Vision, Artificial Intelligence, Computer Science, or a related field</p></li><li><p style="min-height:1.5em"><strong>7+ years of deep learning research experience in computer vision, specializing in non-natural imaging modalities (radar preferred)</strong></p></li><li><p style="min-height:1.5em">Proven expertise in object detection, segmentation, and classification models</p></li><li><p style="min-height:1.5em">Deep familiarity with radar data or non-natural signal modalities like LiDAR, sonar, or medical imaging</p></li><li><p style="min-height:1.5em">Hands-on experience deploying and optimizing models for edge computing hardware</p></li><li><p style="min-height:1.5em">Advanced proficiency in Python and PyTorch</p></li><li><p style="min-height:1.5em">Experience with TensorRT or similar high-performance inference libraries is a strong advantage</p></li><li><p style="min-height:1.5em">Fluent English, both written and spoken</p></li></ul><h2><strong>What we offer</strong></h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Working for a Great Place to Work® certified company;</p></li><li