Humanoid Robotics Engineer

2 days ago


Delhi, Delhi, India MethdAI - The AI Learning Platform Full time
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 ResponsibilitiesRobot 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 QualificationsEducation & 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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