We are seeking a highly skilled and motivated Senior Software Developer with expertise in motion planning, control algorithms, and low-level robot motion. The ideal candidate will play a crucial role in designing, implementing, and optimizing advanced motion systems for our robotics products. As a senior member of the team, you will be responsible for driving innovation and technical excellence in the development of real-time, high-performance software for robotics applications. Key Responsibilities Design and develop robust and scalable motion planning algorithms for autonomous robotic systems, ensuring high levels of accuracy and efficiency. Implement low-level control algorithms for robot motion and manipulation, focusing on real-time performance and precision. Develop Visual Mapping and Localization stack, using classical methods as well as pioneering AI/ML approaches Collaborate closely with hardware teams to optimize control interfaces and ensure seamless communication between software and robotic hardware. Develop GPU accelerated manipulation capabilities for robot arms using cuMotion (preferred), MoveIt2 etc. Enable HD mapless navigation in complex urban scenarios by incorporating enriched BEV models and generate static obstacles and occupancy grids and build occlusion masks to enrich robot navigation scenarios. Analyze and optimize system performance, identifying bottlenecks and developing solutions to improve real-time execution in dynamic environments. Work on sensor fusion algorithms to enhance motion planning, enabling robots to operate in complex and uncertain environments. Integrate and optimize existing algorithms for multi-robot coordination and interaction in shared spaces. Collaborate with cross-functional teams, including perception, AI, and simulation teams, to integrate motion planning and control systems into larger robotic frameworks. Participate in design reviews, code reviews, and testing to ensure high-quality software development. Mentor and guide junior developers, providing technical leadership and fostering a collaborative, knowledge-sharing environment. Troubleshoot and debug motion control systems, quickly identifying and resolving issues related to system performance, stability, and accuracy. Stay up-to-date with the latest advancements in robotics and control theory, incorporating new techniques and technologies into motion planning and control systems. Develop, design, implement, test, and benchmark the robot control software in comparison to SOTA algorithms and (if available) worldwide competitors Contribute to the continuous improvement of the development process, tools, and methodologies used by the team. Lead the integration and testing of motion control systems in real-world robotic applications, ensuring safety and reliability. Required Qualifications Bachelors or Master's degree in Computer Science, Robotics, Electrical Engineering, or related field. Extensive experience in software development with a focus on motion planning, control algorithms, and low-level robotics systems (5+ years). Strong proficiency in programming languages such as C++ (Preferred) , Python, or similar. In-depth knowledge of control theory, optimization techniques, and motion planning algorithms (e.g., RRT, A*, D*). Experience with parallel programming and especially GPU accelerated inference technologies like CUDA, TensorRT etc and experience with ROS 2, including Isaac ROS (preferred), ros2_control, FoundationPose and MoveIt2 Experience with robotic middleware, such as ROS (Robot Operating System), and real-time operating systems (RTOS). Expertise in robotics fundamentals, including geometry, linear algebra, multivariate calculus, kinematics, dynamics etc Strong understanding of robot kinematics, dynamics, and control systems. Familiarity with simulation tools like Gazebo, RViz, or similar, for testing and validating motion algorithms. Hands-on experience with real-time systems and embedded programming. Experience with multi-threaded programming and optimization for high-performance applications. Excellent problem-solving skills and the ability to work under pressure in a fast-paced, dynamic environment. Strong communication skills, with the ability to collaborate effectively across disciplines. Preferred Qualifications Master's degree in Robotics, Control Systems, or a related field. Experience with reinforcement learning and machine learning techniques applied to motion planning and control. Familiarity with advanced motion planning algorithms for multi-agent systems. Experience with hardware-in-the-loop (HIL) testing and integration. Knowledge of distributed systems and cloud-based robotics frameworks. Significant deep learning experience, especially with deployment on NVIDIA embedded platforms of the Jetson family Background in 3D geometry, computer vision, sensor calibration, or state estimation Publications in major computer vision or robotics conferences in a field relevant to deep learning, SLAM, mapping, localization, and perception Familiarity both with the classical, geometric and deep learning aspects of path planning and control
