Chief Embodied AI Systems Designer

2 days ago

Alwar, Rajasthan, India beBeePhysicalAiEngineer Full time US$ 1,50,000 - US$ 2,00,000
Physical AI Engineer

We are seeking a highly skilled Artificial Intelligence specialist to design, develop, and implement advanced control systems for humanoid robots. This role involves integrating vision-language-action models with physical agents to create robots capable of performing complex tasks in dynamic environments.

Key Responsibilities:
  • Integrate machine learning models with physical robots to enable seamless interaction.
  • Design efficient control frameworks that translate AI decision-making into smooth motor actions.
  • Develop pipelines to align simulation-to-reality and optimize robot learning for real-world deployment.
  • Apply multi-modal AI learning (vision, audio, haptics, proprioception) to enhance robot perception and adaptability.
  • Collaborate with hardware teams to calibrate robot sensors, optimize energy efficiency, and ensure reliable AI control execution.
  • Conduct experiments in areas such as human-robot interaction, autonomous navigation, dexterous manipulation, and multi-agent collaboration.
  • Research and implement emerging paradigms in Physical AI, including embodied GPTs, action-conditioned transformers, and world-model-based learning.
Requirements:
  • Bachelor's or Master's degree in Robotics, Mechatronics, Computer Science, AI, or a related field (Ph.D. preferred for senior positions).
  • Strong background in machine learning, particularly reinforcement learning, imitation learning, or embodied AI systems.
  • Hands-on experience with robotics simulation environments (Isaac Sim, MuJoCo, Unity, Gazebo).
  • Proficiency in Python and good knowledge of C++/ROS2 for robotics integration.
  • Deep understanding of robotics control theory, kinematics, and sensor fusion.
  • Demonstrated work with humanoid robots, quadrupeds, or robotic arms, preferably on vision-language-action models.
Favorable Skills:
  • Familiarity with NVIDIA Jetson, CUDA optimization, and real-time robotics inference.
  • Experience with large foundation models adapted for robotics (OpenAI VLA, Google RT-2, Gr00T).
  • Knowledge of safety-critical autonomous systems.
  • Exposure to distributed training of large models on RTX/HPC clusters.
  • Working knowledge of teleoperation frameworks (for collecting demonstration data).
Benefits:
  • The opportunity to work on cutting-edge humanoid robotics with embodied AI.
  • Access to advanced computing infrastructure (NVIDIA RTX 6000 GPUs, Jetson Thor platforms, VR mocap systems, and Unitree robots).
  • A multi-disciplinary team environment spanning AI research and robotics engineering.
  • Growth opportunities for leadership in next-gen Physical AI projects.

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