
Phyiscal AI Engineer
4 hours ago
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
- 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, robotics engineering, and education technology
. - Competitive remuneration and growth opportunities for leadership in
next-gen Physical AI projects
. - Would you like me to position this role more towards
research (academic-style Physical AI exploration)
or towards
product/industry deployment (developing applied humanoid robots for education and enterprise use cases)
?
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