Ota AIRoA (AI Robot Association)
About AIRoA


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.

We are building a shared "robot data ecosystem" where datasets, trained models, and benchmarks are available to everyone.

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.

We invite ambitious researchers and engineers to join us in this bold challenge to rewrite the history of robotics.

Job Description

In this role, you will be responsible for:
Designing and building scalable data collection systems that operate across hundreds of humanoid and mobile robots
Developing semi-autonomous teleoperation systems that ensure low latency, high controllability, and minimal operator workload
Creating automated pipelines to deploy trained models and rigorously evaluate them in both simulation and real-world robotic platforms
Working closely with the Vision-Language-Action (VLA) team to seamlessly integrate and deploy cutting-edge models onto physical robots

Requirements

Required Qualifications

Currently pursuing (or recently completed) a Master's or PhD in Robotics, Mechanical Engineering, Computer Science, or a related field
Solid understanding of robotics concepts and a strong motivation to conduct publishable research
Hands-on experience with physical robots (e.g., manipulators, mobile robots, or robotic platforms used in research labs)
Proficiency in at least one programming language commonly used in robotics (e.g., Python, C++, ROS 1/2)
Ability to work independently as well as collaboratively in a research team

Preferred Qualifications

Prior research experience leading to publications or submissions at robotics/AI conferences (e.g., RSS, CoRL, ICRA, IROS)
Experience with teleoperation systems, including leader-follower architectures, AR, or VR interfaces
Familiarity with control methods such as impedance control, force control, or sim-to-real adaptation
Experience with tactile or force-torque sensing in robotic manipulation tasks
Exposure to high-fidelity simulators (e.g., MuJoCo, PyBullet, Isaac Sim) for robotic training and evaluation

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.

Work location

Tokyo Ryutsu Center A Bldg. AW4-5, 6-1-1 Heiwajima, Ota-ku, Tokyo , Japan
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