Description
About AIRoA
AI Robot Association (AIRoA) is an organization dedicated to advancing the development of generative AI foundation models in the field of robotics by collecting large-scale real-world robot data, including data from humanoid robots.
AIRoA has been selected by Japan’s Ministry of Economy, Trade and Industry (METI) and NEDO under the “Post-5G Information and Communication Systems Infrastructure Enhancement R&D Project” to develop a data platform for generative AI foundation models in robotics. The project has a total budget of JPY 20.5 billion.
Leveraging this foundation, AIRoA is undertaking a project to collect one million hours of humanoid robot operation data using more than 100 robots, and to develop a world-class Vision-Language-Action (VLA) model based on this data.
Responsibilities
- Teleoperation Platform: Design and implement teleoperation systems for humanoid robots, mobile manipulators, and service robots, while continuously improving operability, stability, latency, and recovery performance.
- Demonstration Data Quality: Establish operation logs, sensor logs, failure classifications, reproduction procedures, and data collection workflows to improve the quality of human demonstrations used for imitation learning and VLA evaluation.
- Cross-Functional Collaboration: Work closely with the Autonomy, VLA, Simulation, Integration, and Hardware teams to ensure that teleoperation, control, testing, and real-world robot evaluation operate seamlessly as an integrated system.
- Real-Robot Debugging: Analyze logs related to low-latency communication, control cycles, sensor synchronization, abnormal states, and recovery behavior, and take ownership of reproducing, fixing, and verifying issues on real robots.
Requirements
Required Qualifications
- Hands-on experience controlling or debugging physical robotic systems, such as manipulators, humanoid robots, industrial robots, or service robots.
- Experience in teleoperation, including VR, haptics, force feedback, leader-follower systems, motion capture, puppeteering-based control, or real-time retargeting.
- Experience building robotic systems using ROS or ROS 2, including system integration and system-level analysis of physical robotic systems.
- Ability to persistently troubleshoot hard-to-reproduce issues on physical systems through iterative logging, hypothesis development, reproduction testing, fixes, and validation.
Preferred Qualifications
- Experience implementing robot control, real-time systems, communications, log analysis, or related tools in C or Python.
- Ability to develop systems with careful consideration of interfaces across multiple modules, such as sensors, control, state management, safety stops, UI, data collection, and evaluation environments.
- Experience with learning-based control, including imitation learning, reinforcement learning, hybrid MPC + learning, safety-constrained learning, or deployment of learned controllers.
- End-to-end experience in data collection, including human demonstration collection, operation quality evaluation, failure classification, task specification, evaluation set development, and collaboration with VLA or robot learning teams.
- Experience operating physical robotic systems in areas such as teleoperation, semi-autonomous operation, multi-robot operations, field testing, or long-duration testing.
- Experience with fleet management or production-grade robotic system operations.
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.

