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.
- Robust 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