Principal AI Engineer - Robotics Control (Internal Use)

Description

Summary: Design and implement advanced control algorithms for autonomous robotic platforms, optimizing motion planning and integrating adaptive learning techniques. Highlights: 1. Design advanced control algorithms for autonomous robotic platforms 2. Optimize motion planning for multi-robot coordination 3. Collaborate on integrating control systems with AI and hardware ·       Design and implement advanced control algorithms (e.g., PID, adaptive control, model predictive control) tailored for autonomous robotic platforms. ·       Optimize motion planning and path control strategies to enhance multi-robot coordination and operational efficiency. ·       Develop real-time control architectures that leverage edge computing for low-latency decision-making. ·       Integrate adaptive learning techniques to continuously refine control performance, particularly for dynamic systems. ·       Develop and test control algorithms in both simulation and real-world experiments, utilizing aerial simulation tools (e.g., PX4 SITL, AirSim) when applicable. ·       Collaborate with interdisciplinary teams to integrate control systems with AI, sensor fusion, and hardware subsystems. Requirements Required Qualifications ·       Master’s or PhD in Robotics, Control Systems, or a related field. ·       3+ years of experience in robotics control system development or equivalent R&D experience (PhD candidates with strong research contributions are encouraged to apply). ·       Strong background in control theory, state estimation, and optimization for autonomous systems. ·       Proficiency in C++, Python, and ROS; hands-on experience with real-time control systems is essential. ·       Expertise in traditional model-based control methods is required; familiarity with learning-based control approaches (e.g., reinforcement learning, adaptive control) is a plus. ·       Experience in aerial robotics control—including familiarity with flight dynamics and autopilot systems (e.g., PX4)—is highly desirable. Preferred Qualifications ·       Postdoctoral experience in robotics or control systems. ·       Experience with real-world deployment and flight testing of autonomous systems. ·       A strong research record in control theory, AI-driven robotics, or multi-agent coordination with an emphasis on aerial applications. ·       Proficiency with MATLAB/Simulink for control system design and testing.