R&D-011 Senior Research Scientist (VLAs)

Location: On-site, Heiwajima, Tokyo, Japan
Division: Development Division
Employment Type: Full time

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Overview

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.

AIRoA is committed to making everything open and accessible, building a shared “robot data ecosystem” where datasets, trained models, and benchmarks are available to everyone. Researchers globally can evaluate their models on standardized humanoid robots through our open evaluation platform.

Opportunities include:

• Tackling challenges in robotics and AI, such as multimodal learning, tactile-rich manipulation, sim-to-real transfer, and large-scale benchmarking.
• Access to state-of-the-art infrastructure: humanoid robots, GPU clusters, simulators, and a global-scale evaluation pipeline.
• Collaboration with leading experts in academia and industry and opportunities for high-impact publications.
• Contributing to an initiative redefining 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 to pioneer the next era of robotics.

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Job Description

In this role, you will be responsible for:

• Designing and implementing data preprocessing pipelines for multimodal robot datasets
• Training VLA models using supervised learning, RL, fine-tuning, RLHF, and training from scratch
• Developing and evaluating models in both simulation and on physical robots
• Improving training robustness and efficiency through algorithmic innovation
• Analyzing model performance and proposing enhancements based on empirical results
• Deploying VLA models onto real humanoid and mobile robotic platforms
• Publishing research in top-tier conferences (e.g., NeurIPS, CoRL, CVPR)

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Requirements

Required Qualifications

(All of the following qualifications must be met)

• MS degree with 3+ years of industry experience, or PhD in Computer Science, Electrical Engineering, or a related field.
• Have at least one first-author publication in a top-tier conference such as CoRL, ICML, CVPR, NeurIPS, IROS, ICLR, ICCV, or 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
• Knowledge of the latest advancements in large-scale machine learning research
• 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.
• 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)
• Strong end-to-end system building and rapid prototyping skills
• Experience with robotics frameworks like ROS

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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.

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Work location:
Tokyo Ryutsu Center A Bldg. AW4-5/4-6, 6-1-1 Heiwajima, Ota-ku, Tokyo 143-0006, Japan