Role Overview

We are seeking a highly motivated and skilled Navigation Engineer to contribute to the development of advanced autonomous navigation capabilities for Unmanned Ground Vehicles (UGVs). This role focuses on designing, implementing, and optimizing planning and control systems for autonomous operation across diverse environments, including off-road terrain, urban settings, and highway scenarios.

The ideal candidate possesses strong expertise in control theory, motion planning, mathematical modeling, system identification, and optimization, combined with hands-on experience developing and validating autonomous navigation solutions in real-world applications. Experience with learning-based control techniques and intelligent decision-making frameworks is highly desirable.

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.