About this role
Deep Learning Engineer (Radar Computer Vision) Robin Radar Systems Software Engineering, Data Science Posted on Aug 28, 2026 Turn complex radar data into clear detections - so our software can spot birds, drones, and airborne threats in real time. 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. Reporting to the AI Lead, your models directly power live radar systems across the globe. What you'll do - Framework design and architecture: 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. - Data strategy and label management: Develop innovative strategies to handle imperfect, sparse, or missing radar labels. Automate dataset creation and labeling workflows to keep research moving fast. - Model optimization for the edge: Optimize neural networks using TensorRT for real-time, low-latency inference. Ensure every model runs smoothly on edge hardware deployed in the field. - Cross-functional integration: 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. What you bring - Master's degree in Computer Vision, Artificial Intelligence, Computer Science, or a related field - 5+ years of professional experience in deep learning research for computer vision - Proven expertise in object detection, segmentation, and classification models - Deep familiarity with radar data or non-natural signal modalities like LiDAR, sonar, or medical imaging - Hands-on experience deploying and optimizing models for edge computing hardware - Advanced proficiency in Python and ...