Humanoid Robotics Engineer

Position Overview We are seeking a skilled Humanoid Robotics Engineer to lead the training, development, and commercial deployment of advanced humanoid robots, including Unitree G1, H1, and similar platforms. This role focuses on advancing AI-driven learning capabilities, implementing reinforcement learning algorithms, and preparing humanoid systems for real-world commercial applications across manufacturing, logistics, healthcare, and service industries. Key Responsibilities Robot Training & Development Design and implement reinforcement learning (RL) control routines for humanoid robot locomotion, manipulation, and task execution. Develop imitation learning algorithms to enable robots to learn complex behaviours through human demonstration. Create and optimise sim-to-real transfer protocols using Isaac Gym, MuJoCo, and other simulation platforms. Implement Vision-Language-Action (VLA) models for natural human-robot interaction and instruction-following capabilities. Commercial Application Development Deploy humanoid robots in manufacturing environments for assembly, quality control, and material handling tasks. Configure robots for logistics and warehousing  operations, including inventory management, order fulfilment, and last-mile delivery. Adapt systems for retail and customer service applications with a focus on safety and user experience. Develop hazardous environment applications for inspection, maintenance, and emergency response scenarios. Technical Implementation Program and calibrate 23-43 DOF humanoid systems with advanced dexterous manipulation capabilities Integrate 3D LiDAR, depth cameras, and tactile sensor arrays for enhanced environmental perception. Implement whole-body control systems for balanced locomotion and coordinated upper/lower body movements. Optimise battery management and power efficiency for extended operational periods (2-4+ hours) AI & Machine Learning Develop and tune deep reinforcement learning models using frameworks like PyTorch and TensorFlow. Create behaviour trees and decision-making algorithms for autonomous task planning. Implement SLAM (Simultaneous Localisation and Mapping) and navigation systems. Design object recognition and manipulation strategies using computer vision and tactile feedback. Required Qualifications Education & Experience Bachelor's degree in Robotics Engineering, Mechatronics, Computer Science, Electrical/Mechanical Engineering, or related field. 3+ years of hands-on experience with humanoid or bipedal robotics systems. 2+ years of experience with reinforcement learning and machine learning applications in robotics. Technical Skills Expert proficiency in Python, C++, and ROS 2 for robotics development. Advanced knowledge of reinforcement learning frameworks (Isaac Gym, OpenAI Gym, Stable Baselines). Experience with simulation platforms: MuJoCo, Gazebo, NVIDIA Isaac, Unreal Engine. Proficiency in machine learning libraries: PyTorch, TensorFlow, scikit-learn. Strong background in control theory, kinematics, dynamics, and motion planning. Hands-on experience with sensor integration (LiDAR, cameras, IMUs, tactile sensors). Specialized Knowledge Deep understanding of humanoid robot mechanics, joint control, and balance systems. Experience with force-position hybrid control and impedance control for manipulation tasks. Knowledge of commercial deployment challenges, including safety protocols and regulatory compliance Familiarity with Unitree robotics platforms (G1, H1 series) and their development ecosystems Preferred Qualifications Master's degree in Robotics or related field with thesis focus on humanoid systems. Experience with NVIDIA GR00T platform and humanoid development workflows. Previous commercial deployment experience in manufacturing, logistics, or service robotics. Knowledge of industry standards and safety regulations for human-robot collaboration. Publication record in robotics conferences or journals. Work Environment Laboratory and workshop settings for development and testing. Manufacturing facilities for deployment and field testing. Collaborative environment working with mechanical, electrical, and software engineering teams. Travel is required for on-site deployments and customer support.

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