Robotics & AI algorithm engineer

Are you passionate about autonomous technology, AI, and advanced sensing systems? Axon Pulse is excited to welcome a skilled Robotics & AI Engineer to our Autonomous Team.At Axon Pulse, we're at the forefront of signal processing and AI innovation. Join us in shaping the future of autonomy by developing state-of-the-art perception and decision-making technologies.About the RoleWe are seeking an experienced Robotics & AI Engineer with a strong background in autonomous perception, deep learning, and sensor fusion. In this role, you will develop both AI-driven and classic algorithms, working with diverse sensors, such as cameras, radars, and LIDAR. This position offers the opportunity to create real-world, mission-critical autonomous systems and directly influence cutting-edge defence and robotics technologies.ResponsibilitiesDesign, develop, and optimize real-time perception and sensor fusion algorithms for autonomous systems.Integrate algorithms into ROS2-based autonomy stacks, working closely with cross-functional teams.Train, evaluate, and refine deep learning models to achieve robust performance in real-time autonomous systems.Lead data collection, curation, and labelling strategies to build robust, high-quality datasets.Collaborate closely with defence industry clients to tailor solutions to their specific needs and specifications.Qualifications:5+ years of experience in autonomous perception, sensor fusion, tracking, and computer vision.2+ years of hands-on experience in Deep Learning and Computer Vision (designing, training, and deploying models).Strong background in Optimization techniques and Signal Processing algorithms.Practical experience with ROS2.Proficiency in Python and related deep learning frameworks (e.g., PyTorch, TensorFlow).Bachelor's degree in Electrical Engineering, Computer Science, Robotics, or a related field (Master’s preferred).Nice to Have Experience Autonomous robotics or vehicle applications.Radar or LIDAR sensing technologies.Sensors calibrationAlgorithm deployment on embedded hardware or edge devices.