The AI Robot Association (AIRoA) is launching a groundbreaking initiative: collecting one million hours of humanoid robot operation data with hundreds of robots, and leveraging it to train the world's most powerful Vision-Language-Action (VLA) models.
What makes AIRoA unique is not only the unprecedented scale of real-world data and humanoid platforms, but also our commitment to making everything open and accessible.
Researchers around the world will be able to evaluate their models on standardized humanoid robots through our open evaluation platform.
For researchers, this means an opportunity to:
Work on fundamental challenges in robotics and AI: multimodal learning, tactile-rich manipulation, sim-to-real transfer, and large-scale benchmarking
Access state-of-the-art infrastructure: hundreds of humanoid robots, GPU clusters, high-fidelity simulators, and a global-scale evaluation pipeline
Collaborate with leading experts across academia and industry, and publish results that will shape the next decade of robotics
Contribute to an initiative that will redefine the future of embodied AI—with all results made open to the world
As we prepare for our official launch on October 1, 2025, we are assembling a world-class team ready to pioneer the next era of robotics.
Job Description
In this role, you will be responsible for:
Design and implement data preprocessing pipelines for multimodal robot datasets
Train VLA models using supervised learning, RL, fine-tuning, RLHF, and training from scratch
Develop and evaluate models in both simulation and on physical robots
Improve training robustness and efficiency through algorithmic innovation
Analyze model performance and propose enhancements based on empirical results
Deploy VLA models onto real humanoid and mobile robotic platforms
Publish research in top-tier conferences (e.g., NeurIPS, CoRL, CVPR)
Requirements
Required Qualifications
(All Of The Following Qualifications Must Be Met)
MS or PhD in Computer Science, Electrical Engineering, or a related field
Proven track record of achieving significant results as demonstrated by publications at leading conferences in Machine Learning (NeurIPS, ICML, ICLR), Robotics (ICRA, IROS, RSS, CoRL), and Computer Vision (CVPR, ICCV, ECCV)
Experience with open-ended learning, reinforcement learning, and frontier methods for training LLMs/VLMs/VLAs such as RLHF and reward function design
Experience working with simulators or real-world robots
Experience with deep learning frameworks such as PyTorch
Preferred Qualifications
PhD or equivalent research experience in robot learning
Practical experience implementing advanced control strategies on hardware, including impedance control, adaptive control, force control, or MPC
Experience using tactile sensing for dexterous manipulation and contact-rich tasks
Familiarity with simulation platforms and benchmarks (e.g., MuJoCo, PyBullet, Isaac Sim) for training and evaluation
Strong end-to-end system building and rapid prototyping skills
Experience with robotics frameworks like ROS
Benefits
There are currently no comparable projects in the world that collect data and develop foundation models on such a large scale.
As mentioned above, this is one of Japan's leading national projects, supported by a substantial investment of 20.5 billion yen from NEDO.
This position will play a crucial role in determining the success of the project.You will have broad discretion and responsibility, and we are confident that, if successful, you will gain both a great sense of achievement and the opportunity to make a meaningful contribution to society.
Furthermore, we strongly encourage engineers to actively build their careers through this project—for example, by publishing research papers and engaging in academic activities.
Tokyo Ryutsu Center A Bldg. AW4-5, 6-1-1 Heiwajima, Ota-ku, Tokyo , Japan
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