Role Overview
- A CLPS company is seeking a Engineer
- Robotics Controls to develop, simulate, test, and deploy control algorithms for robotic and autonomous systems. The role focuses on robot dynamics, motion control, simulation, Sim-to-Real deployment, and Hardware-in-the-Loop (HIL) / Software-in-the-Loop (SIL) validation.

Key Responsibilities
-
• Develop and implement robot motion and control algorithms for robotic and autonomous systems.
• Develop controllers for position, velocity, torque, trajectory tracking, and stabilization.
• Model and simulate robot kinematics, dynamics, actuators, and system behavior.
• Develop and validate algorithms in simulation before deployment on physical hardware.
• Perform Sim-to-Real transfer of control algorithms and identify and compensate for differences between simulation and real-world systems.
• Develop and execute Software-in-the-Loop (SIL), Model-in-the-Loop (MIL), and Hardware-in-the-Loop (HIL) testing.
• Integrate control algorithms with sensors, actuators, embedded controllers, and robotic platforms.
• Perform system identification, parameter estimation, calibration, and controller tuning.
• Develop sensor-fusion and state-estimation solutions for reliable robot control.
• Analyze system performance using experimental data and implement improvements.
• Support hardware bring-up, debugging, field testing, and validation of control systems.
• Develop automated testing and regression-testing workflows for robotic control software.
• Document algorithms, simulation models, test procedures, results, and system configurations.
• Collaborate with mechanical, electrical, embedded, perception, and software teams during system integration. Required Skills & Qualifications
-




• Strong programming skills in C++ and Python.
• Good understanding of:
• Control systems, Robot kinematics and dynamics, State-space modelling
• Trajectory generation and tracking
• Feedback control, PID control
• Linearization
• State estimation
• Practical experience with ROS 2 and Linux.
• Experience developing and testing control algorithms in simulation.
• Understanding of SIL, MIL, and HIL testing methodologies.
• Solid mathematical and analytical problem-solving skills. Simulation & Control Tools
- Experience with one or more of:
• MATLAB/Simulink
• NVIDIA Isaac Sim / Isaac Lab
• Gazebo
• MuJoCo
• CoppeliaSim
• ROS 2 simulation frameworks Preferred Skills
-
• Knowledge of model-based control, optimal control, MPC, adaptive control, nonlinear control, as well as data-driven and learning-based controls.
• Knowledge of sensor fusion, Kalman filtering, EKF/UKF, and state estimation.
• Experience with robot hardware, actuator modelling, embedded controllers, motors, encoders, IMUs, and other sensors.
• Familiarity with real-time systems and embedded control.
• Experience with Sim-to-Real deployment on physical robotic systems.
• Experience with Docker, Git, automated testing, and CI/CD.
• Exposure to reinforcement learning and imitation learning is desirable.
• Experience deploying control algorithms on NVIDIA Jetson, ARM-based computers, or other edge platforms is advantageous.
• Experience with mobile robots, manipulators, autonomous vehicles, or space/field robotic systems is desirable. Qualification
- B.
E./B.
Tech. or M.
E./M.
Tech. in Robotics, Electrical/Electronics, Mechanical, Mechatronics, Aerospace Engineering, or related discipline.

📌 Control System Engineer (India)
🏢 Rail Labs
📍 India