Regulus is an agile defense-tech startup tackling the most complex challenges in counter-drone and uncrewed defense. With hundreds of combat-proven systems deployed by the IDF and global partners, we are now engineering the next generation of C-UxS (Counter-Uncrewed Systems). We leverage advanced electronic warfare and kinetic measures to detect and neutralize hostile threats. If you want to push technological boundaries while safeguarding Israel and our allies, join us at this pivotal stage of our growth. If you're looking for a role that combines deep technology, ownership, and real-world impact - this is your opportunity. You'll work on 0→1 development of next-generation computer vision capabilities, addressing operational challenges for which no proven solutions currently exist. Key Responsibilities: Drive end-to-end computer vision solutions from concept and research through deployment and operational validation Develop detection, classification, and tracking algorithms Improve performance on small and distant aerial targets Build and maintain training datasets and evaluation tools Optimize models for real-time operational performance Collaborate with software, hardware, and systems engineering teams Requirements Strong background (5+ years experience) in computer vision and deep learning Proven ability to independently design, develop, and deliver computer vision solutions from scratch Hands-on experience with detection and tracking models (YOLO, Faster R-CNN, DETR, DeepSORT, ByteTrack, or similar) Experience processing real-time video from EO/IR, thermal, or surveillance cameras Proficiency in Python with PyTorch or TensorFlow Experience across the full ML pipeline: data collection, annotation, training, and evaluation Ability to optimize models for real-time inference on edge devices (NVIDIA Jetson, GPU servers, embedded platforms) Familiarity with small-object and long-range detection, image enhancement, and low-SNR conditions Working knowledg
