Robotics Control Engineer – Humanoid Robots

Robotics Control Engineer – Humanoid Robots

CNTXT AI | Abu Dhabi, UAE | Full-Time, On-Site | Robotics & Embodied AI | 5+ Years

About CNTXT AI

CNTXT AI is an Abu Dhabi-based Data & AI company delivering advanced artificial intelligence, robotics, and data solutions to technology companies, enterprises, and government organizations globally. Our capabilities include robotics and embodied AI, AI training data, machine learning, computer vision, and human demonstration data collection.

About the Role

We are seeking a hands-on Robotics Control Engineer to design, implement, and optimize control algorithms that enable humanoid robots to balance, walk, manipulate objects, and operate reliably in real-world environments. You will work directly with physical robots, actuators, sensors, embedded systems, and simulation platforms, collaborating with robotics, VLA, AI, and hardware teams.

Key Responsibilities

Humanoid Robot Control Systems

• Design and implement joint-level, task-space, and whole-body controllers for humanoid platforms.
• Develop position, velocity, torque, and impedance control strategies.
• Integrate controllers with robot hardware and improve stability, responsiveness, and reliability.

Whole-Body Control & Robot Dynamics

• Implement inverse kinematics, inverse dynamics, and optimization-based control.
• Use quadratic programming and other methods to manage contact forces, joint constraints, and actuator limits.
• Coordinate arms, legs, torso, and hands during complex movements.

Locomotion, Balance & Motion Planning

• Develop walking, standing, gait generation, footstep planning, and trajectory optimization.
• Implement Model Predictive Control (MPC), posture stabilization, disturbance rejection, and recovery strategies.
• Improve dynamic locomotion across changing surfaces and operating conditions.

Robotic Manipulation & Motion Control

• Develop trajectory tracking, force control, compliant manipulation, and bimanual coordination.
• Improve grasping, object handling, and contact-rich task execution.
• Connect VLA or learned policies to reliable low-level robotic controllers.

Real-Time Control & Hardware Integration

• Integrate motors, actuators, encoders, IMUs, and force/torque sensors.
• Optimize control frequency, latency, hardware communication, and computational efficiency.
• Support calibration, commissioning, joint limits, and emergency-stop safety mechanisms.

Simulation & Sim-to-Real

• Build and validate control systems in Isaac Sim, Isaac Lab, MuJoCo, Gazebo, or similar tools.
• Validate dynamic models and control behavior before physical deployment.
• Reduce sim-to-real gaps and establish repeatable testing procedures.

Learning-Based Control

• Integrate reinforcement learning and imitation learning policies with model-based controllers.
• Work with AI researchers on learned locomotion and manipulation.
• Evaluate robustness and implement safety constraints and fallback behaviors.

State Estimation & Sensor Integration

• Integrate IMUs, joint encoders, force sensors, and proprioceptive feedback.
• Develop sensor fusion for orientation, velocity, position, and contact-state estimation.
• Investigate calibration, noise, and estimation instability.

Testing, Validation & Collaboration

• Benchmark stability, movement accuracy, latency, repeatability, and task completion.
• Analyze physical robot experiments, troubleshoot failures, and document improvements.
• Collaborate with hardware engineers, VLA engineers, AI researchers, and robotics operations.

Requirements

• 5+ years of professional experience in robotics control, motion control, autonomous systems, or related engineering.
• Bachelor’s or Master’s degree in Robotics, Mechanical Engineering, Electrical Engineering, Mechatronics, Computer Science, or related field.
• Advanced proficiency in C++ and Python; experience with ROS/ROS2 and Linux.
• Strong knowledge of robot kinematics, dynamics, control theory, PID, impedance control, inverse kinematics, and trajectory tracking.
• Knowledge of MPC, optimization-based control, or whole-body control.
• Experience with multi-DOF robotic systems, actuators, sensors, motor controllers, and hardware interfaces.
• Experience with robotics simulation, real-time systems, and deploying algorithms on physical robots.
• Strong debugging, analytical, problem-solving, and cross-functional communication skills.

Preferred Qualifications

• Direct experience with humanoid or bipedal robots, dynamic walking, and balance.
• Experience with QP-based control, trajectory optimization, rigid-body dynamics, and contact mechanics.
• Familiarity with Pinocchio, Drake, Crocoddyl, MuJoCo, NVIDIA Isaac Sim or Isaac Lab.
• Experience with real-time Linux, EtherCAT, CAN, torque-controlled actuators, and high-frequency control loops.
• Experience with dexterous manipulation, bimanual control, reinforcement learning, and learned policy integration.
• Experience with state estimation, sensor fusion, research publications, or open-source robotics contributions.

Key Performance Indicators

• Stability and reliability of humanoid control systems; walking and balance performance.
• Accuracy and repeatability of motion, manipulation, and task execution.
• Control latency, execution errors, and robustness across operating conditions.
• Successful physical robot integration and simulation-to-real deployment.
• Achievement of engineering milestones, test coverage, and documentation quality.

What Success Looks Like in the First 90 Days

Days 1–30 | Assessment & Familiarization

• Review humanoid hardware, control software, sensors, and existing locomotion/manipulation capabilities.
• Establish baseline benchmarks and identify priority improvements.

Days 31–60 | Development & Integration

• Implement and simulate selected control improvements.
• Integrate controllers on physical robots and demonstrate measurable gains.

Days 61–90 | Validation & Optimization

• Validate balance, locomotion, and manipulation performance on physical robots.
• Optimize stability and latency; present results and a six-month development roadmap.

Why Join CNTXT AI?

Work directly on advanced humanoid robots and next-generation control systems. Collaborate with robotics engineers, VLA specialists, and AI researchers while helping build CNTXT AI’s robotics and embodied AI capabilities in Abu Dhabi.

CNTXT AI • Robotics & Embodied AI • Abu Dhabi, UAE