Join Aeronautics – A Cutting-Edge Leader in Navigation & Autonomous Systems Development!

Aeronautics, a subsidiary of Rafael, is at the forefront of technological innovation, developing advanced systems in one of the most dynamic and rapidly evolving fields. We are committed to continuous technological advancement and pushing the boundaries of what’s possible.

Objective:

Establish and lead the development of computer vision capabilities for UAV-based navigation and mission applications, including perception, tracking, and scene understanding, in collaboration with existing navigation and systems teams.

Key Responsibilities:

• Develop and implement real-time computer vision algorithms to support UAV navigation, mission execution, and autonomy.
• Integrate vision-based solutions (e.g., visual odometry, SLAM) with traditional navigation subsystems such as INS/GNSS.
• Design, train, and deploy deep learning models for mission-relevant tasks including terrain classification, obstacle avoidance, and target recognition.
• Work closely with System Engineers, Navigation alg developers and SW developers teams to deploy CV solutions on resource-constrained platforms (e.g., Jetson).
• Lead field integration and testing efforts, ensuring reliability and robustness in real-world conditions.

Required Qualifications:

• B.Sc. or M.Sc. in Computer Science, Electrical Engineering, Robotics, or a related discipline.
• Minimum 3 years of hands-on experience developing computer vision systems, preferably in real-time or embedded robotics environments.
• Strong proficiency in Python and C++, with experience using OpenCV, PyTorch, and TensorRT.
• Deep understanding of camera modeling, calibration, and algorithms such as:
• Visual Odometry
• Visual SLAM
• Optical Flow
• Structure from Motion (SfM)
• Experience integrating vision with other sensor modalities (e.g., IMU, GPS) for perception and navigation tasks.

Preferred Qualifications:

• Experience with Visual-Inertial Odometry (VIO) or vision-aided Kalman filtering.
• Background in UAVs, autonomous navigation, or robotics
• Deploying algorithms on embedded targets.
• Practical experience with deployment on edge computing hardware (e.g., NVIDIA Jetson, Xavier, Orin).
• Familiarity with mission scenarios such as GPS-denied navigation, autonomous landing, or onboard target tracking.

Leadership & Collaboration:

Capable of initiating and leading a focused computer vision team from the ground up.

Excellent communication and coordination skills for cross-functional work with algorithm, system, and embedded engineers.

Ability to define vision roadmap, mentor junior engineers, and deliver solutions aligned with company goals.

Initial Goals:

• Prototype visual odometry and terrain classification module.
• Integrate with existing INS/GNSS navigation system for vision-aided navigation.
• Deliver mission-specific vision capabilities: e.g., moving target tracking.
• Ensure robustness under GPS-degraded and visually challenging environments.