top of page
横組(白).png

​採用・募集

私たちはPhysical AIの領域において世界をリードするために、多くのロボットを活用したデータ収集やロボット基盤モデルの開発の研究を加速しています。

下記のポジションへの応募をご希望の方は下記フォームからご応募ください。

ご応募は随時受け付けており、順次選考を進めています。あなたの経歴が次の採用グループに合致すると判断した場合、こちらから直接ご連絡いたします。

  • 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.

    Required Qualifications

    • MS degree with 3+ years of industry experience, or PhD in Robotics, Mechanical Engineering, Computer Science, or a related field.

    • Extensive hands-on experience with physical robotic systems (e.g., mobile manipulators, humanoids).

    • Deep knowledge of teleoperation systems, including leader–follower architectures, AR, or VR interfaces.

    • Strong programming proficiency in C++, Python, and ROS 1/2.

    Preferred Qualifications

    • PhD or equivalent research experience in robot learning.

    • Strong publication record at top-tier robotics venues (e.g., RSS, CoRL, Science Robotics, TRO, IJRR).

    • 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.

    • Prior experience leading or contributing to large-scale robot data collection initiatives.

    • Familiarity with simulation platforms and benchmarks (e.g., MuJoCo, PyBullet, Isaac Sim) for training and evaluation.

    Others (linguistic qualification, etc.)

     English proficiency at business level is highly appreciated.

    Expeceted Annual Income

    It will be determined according to your ability

    Work location

    Tokyo, Japan

    Working Style

    Discretionary labor system (employees have discretion in how they allocate their working hours to perform assigned duties)

    Holidays Paid Leave

    More than 30 days per year in addition to Saturdays and Sundays (including national holidays and year-end/New Year holidays designated by the company)

    Social insurance

    Full coverage under the Japanese social insurance system (health insurance, employees’ pension, employment insurance, workers’ compensation)

    Commuting

    Commuting allowance provided in accordance with company regulations

    Office perks

    Complimentary snacks and beverages are available in the office

    Side jobs

    Permitted outside of working hours (notification required; restrictions may apply for health, confidentiality, or competitive reasons)

    Visa sponsorship

    Full support for obtaining and maintaining a work visa for international employees

    Relocation support

    Assistance with relocation expenses, including airfare, travel costs, and temporary accommodation upon arrival in Japan

  • 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:

    • 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)

    Required Qualifications

    • MS degree with 3+ years of industry experience, or PhD in Computer Science, Electrical Engineering, or a related field.

    • 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.

    Others (linguistic qualification, etc.)

    【Highly appreciated】
    English proficiency at business level

    Expeceted Annual Income

    It will be determined according to your ability

    Work location

    Tokyo, Japan

    Working Style

    Discretionary labor system (employees have discretion in how they allocate their working hours to perform assigned duties)

    Holidays Paid Leave

    More than 30 days per year in addition to Saturdays and Sundays (including national holidays and year-end/New Year holidays designated by the company)

    Social insurance

    Full coverage under the Japanese social insurance system (health insurance, employees’ pension, employment insurance, workers’ compensation)

    Commuting

    Commuting allowance provided in accordance with company regulations

    Office perks

    Complimentary snacks and beverages are available in the office

    Side jobs

    Permitted outside of working hours (notification required; restrictions may apply for health, confidentiality, or competitive reasons)

    Visa sponsorship

    Full support for obtaining and maintaining a work visa for international employees

    Relocation support

    Assistance with relocation expenses, including airfare, travel costs, and temporary accommodation upon arrival in Japan

  • 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 interns, this means an extraordinary opportunity to:

    • Learn by doing: Tackle real challenges in robotics and AI, such as multimodal learning, tactile-rich manipulation, and sim-to-real transfer.

    • Access cutting-edge infrastructure: Work with humanoid robots, GPU clusters, high-fidelity simulators, and a global-scale evaluation pipeline.

    • Go beyond the classroom: Use infrastructure that is rarely accessible in university labs—a million hours of data, hundreds of humanoid robots, and large-scale computing resources.

    • Grow as a researcher: Collaborate with leading experts, contribute to publications at top conferences, and gain hands-on experience that few labs can offer.

    • Publish with purpose: Engage in project-based research with the clear goal of writing and submitting papers.

    • Make a global impact: Your work will feed into an open initiative that empowers the entire robotics community and shapes the future of embodied AI.

    Job Description

    As a research intern, you will actively engage in cutting-edge robotics research with the clear goal of producing publishable results. Interns are expected to lead or co-author a research paper for submission to top international conferences such as RSS, CoRL, ICRA, or IROS. In addition, your work may also contribute to the development of our open robotic data ecosystem, ensuring broader impact.

     

    Projects are carefully selected to align your expertise with our research objectives, creating opportunities for meaningful academic contributions.

    Sample Projects

    Sample research directions include:

    • Advancing teleoperation through leader–follower architectures, AR, and VR, focusing on reduced latency, higher control fidelity, and lower operator workload.

    • Applying tactile and force–torque sensing to develop novel force-control methods within Vision–Language–Action (VLA) frameworks.

    • Designing techniques for real-time tactile and force feedback to operators, improving human–robot interaction.

    • Building high-fidelity simulators and leveraging them to develop robust sim-to-real transfer methods.

    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.

    Others (linguistic qualification, etc.)

     English proficiency at business level is highly appreciated.

    Expeceted Annual Income

    It will be determined according to your ability

    Work location

    Tokyo, Japan

    Working Style

    Flextime or discretionary work system

    Holidays Paid Leave

    Two-day weekend system. Annual paid leave provided in accordance with laws and regulations.

  • 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 interns, this means an extraordinary opportunity to:

    • Learn by doing: Tackle real challenges in robotics and AI, such as multimodal learning, tactile-rich manipulation, and sim-to-real transfer.

    • Access cutting-edge infrastructure: Work with humanoid robots, GPU clusters, high-fidelity simulators, and a global-scale evaluation pipeline.

    • Go beyond the classroom: Use infrastructure that is rarely accessible in university labs—a million hours of data, hundreds of humanoid robots, and large-scale computing resources.

    • Grow as a researcher: Collaborate with leading experts, contribute to publications at top conferences, and gain hands-on experience that few labs can offer.

    • Publish with purpose: Engage in project-based research with the clear goal of writing and submitting papers.

    • Make a global impact: Your work will feed into an open initiative that empowers the entire robotics community and shapes the future of embodied AI.

    Job Description

    As a research intern, you will actively engage in cutting-edge VLA research with the clear goal of producing publishable results. Interns are expected to lead or co-author a paper submitted to top venues such as CoRL, RSS, ICRA, or NeurIPS. Your work will advance our open VLA ecosystem including contributing datasets, code, and reproducible benchmarks that enable broader community impact. Projects are scoped to align your strengths (e.g., multimodal learning, RL/RLHF, simulation, or on-robot deployment) with our research roadmap, creating meaningful opportunities for academic contribution and real-world validation.

    Sample Projects

    Sample projects include:

    • Curating and aligning VLA datasets from teleoperation logs; building lightweight preprocessing tools and data quality checks for rapid VLA iteration.\

    • Prototyping small-to-medium VLA models (from scratch and fine-tuning) with supervised/RL/RLHF loops; benchmarking ablations for robustness and efficiency.

    • Designing sim-to-real evaluation tasks in MuJoCo/Isaac Sim; scripting domain randomization and transfer baselines, then validating on a mobile or manipulator platform.

    Required Qualifications

    • MS or PhD in Computer Science, Electrical Engineering, or a related field.

    • 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.

    • 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

    Others (linguistic qualification, etc.)

     English proficiency at business level is highly appreciated.

    Expeceted Annual Income

    It will be determined according to your ability

    Work location

    Tokyo, Japan

    Working Style

    Flextime or discretionary work system

    Holidays Paid Leave

    Two-day weekend system. Annual paid leave provided in accordance with laws and regulations.

bottom of page