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.