Job description
 
                         We are seeking a  Physical AI Engineer  to design, develop, and implement AI-driven control and decision-making systems for humanoid robots and embodied agents.
This role involves integrating  vision-language-action models, reinforcement learning, imitation learning, and real-time robotics systems  to create robots capable of performing complex tasks in dynamic environments.
Key Responsibilities
Integrate  AI models (transformers, diffusion policy networks, LLMs, vision-language models)  with physical humanoid robots.
Design real-time  control frameworks  that enable AI decision-making to translate into smooth, safe, and efficient motor actions.
Develop pipelines to align  simulation-to-reality (sim2real)  and optimise 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, optimise energy efficiency, and ensure reliable AI control execution.
Develop  safety protocols  for autonomous decision-making in environments with humans.
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.
Required Qualifications
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.
Preferred Skills
Familiarity with  NVIDIA Jetson, CUDA optimisation, 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).
What We Offer
Salary Range:  ₹15-20 LPA (Lakhs per annum)
The chance 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.
Competitive remuneration and growth opportunities for leadership in  next-gen Physical AI projects .
 
                    
                    
Required Skill Profession
 
                     
                    
                    Engineers