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 Role
We 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.
Responsibilities
- Design, 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 calibration
- Algorithm deployment on embedded hardware or edge devices.