Engineer - Navigation (m/f/d)

Role Overview

Key Responsibilities

• Design, develop, and optimize navigation, planning, and control algorithms for high-performance autonomous ground vehicles.
• Develop accurate mathematical models of vehicle dynamics for simulation, analysis, and real-time implementation.
• Implement advanced control strategies, including adaptive, robust, and predictive control methods, to ensure reliable operation in dynamic and uncertain environments.
• Research, evaluate, and integrate learning-based approaches such as neural network-based system identification and reinforcement learning techniques.
• Integrate navigation solutions with perception, localization, and vehicle software architectures to achieve seamless autonomous operation.
• Conduct simulation, field testing, and performance validation of navigation and control systems.
• Analyze experimental results and system performance to continuously improve accuracy, robustness, safety, and efficiency.
• Develop and maintain technical documentation, including system designs, algorithms, performance analyses, and test reports.

Required Qualifications

• Master's or PhD degree in Robotics, Control Engineering, Electrical Engineering, Computer Science, Applied Mathematics, or a related discipline.
• Strong theoretical and practical knowledge of motion planning, vehicle control, and autonomous navigation systems.
• Expertise in classical and modern control methods, including control system design, analysis, and optimization.
• Experience with mathematical modeling and system identification techniques.
• Strong programming skills in C++.
• Hands-on experience with ROS/ROS2 and navigation frameworks such as Nav2.
• Strong analytical, problem-solving, troubleshooting, and debugging capabilities.
• Excellent communication and technical writing skills, with the ability to work effectively in multidisciplinary engineering environments.

Preferred Qualifications

• Experience with optimization and control frameworks such as CasADi, ACADOS, or similar tools.
• Knowledge of learning-based control methodologies and neural network-based system identification.
• Experience applying reinforcement learning techniques to autonomous navigation and decision-making problems.
• Familiarity with simulation environments and autonomous systems validation workflows.
• Engineer - Navigation in Abu Dhabi, United Arab Emirates