Robotics Control Engineer

About the Role 

Micropolis Robotics is looking for a Senior Robotics Control Engineer to join our growing team and contribute to the development of cutting-edge autonomous systems. In this role, you will work alongside a multi-disciplinary team to develop advanced control algorithms and system architectures for complex robotic platforms. Your work will play a key role in improving the precision, stability, and intelligence of our robotic systems in real-world applications. 

Responsibilities 

• Design, develop, and optimize control algorithms for autonomous robotic systems, ensuring robustness and reliability. 

• Implement real-time motion control and trajectory planning techniques for robotic platforms. 

• Deliver high-quality C++/Python code for real-world robotic applications and simulation environments. 

• Debug and test control and motion control and planning algorithms in both simulation and real-world environments. 

• Work with ROS2 to integrate control systems with the overall robotics stack. 

• Develop and integrate Advanced Control strategies for dynamic robotic systems. 

• Optimize software performance for real-time embedded and high-performance computing platforms. 

• Collaborate with cross-functional teams including perception, planning, and hardware engineers to ensure seamless system performance. 

• Work with Single-Board Computers (NVIDIA Jetson, Raspberry Pi, etc.) to deploy control algorithms on real hardware. 

Requirements 

• 5+ years of experience in robotic control systems and software development. 

• Strong understanding of control theory, kinematics, and dynamics of robotic systems. 

• Experience with model-based control design, system identification, and feedback control techniques. 

• Proficiency in C++ and Python for robotic system development. 

• Hands-on experience with ROS2 and real-world deployment on robotic platforms. 

• Strong problem-solving skills and ability to work in a fast-paced environment. 

• Ability to work independently and within a collaborative, cross-functional team. 

Preferred Qualifications 

• Master’s or Ph.D. in Robotics, Control Systems, Mechatronics, Aerospace Engineering, or related fields. 

• Experience with machine learning-based control techniques. 

• Familiarity with hardware-in-the-loop (HIL) and software-in-the-loop (SIL) testing. 

• Previous experience in autonomous vehicle development.