R&D-029 AI Engineer (VLAs)

AI Robot Association· Development Division
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📍 Heiwajima, Tokyo, JapanFull time

About this role

※日本語版が続きたす。

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.

Job Description

  • Develop Vision-Language models, or equivalent multimodal models, with a view toward applications in the robotics domain
  • Fine-tune existing models, conduct evaluations, perform error analysis, and improve performance
  • Build training pipelines using real-world data, design evaluation metrics, and operate iterative improvement cycles
  • Prepare and preprocess data, and build training environments for image, video, language, and action data
  • Research the latest trends in technologies and academic studies, select appropriate technologies, and incorporate findings into model improvements
  • Establish training infrastructure, inference infrastructure, and experimental environments for real-world model deployment
  • Collaborate with related teams such as software engineers and robotics engineers to define requirements, design validation plans, and drive development

AIRoAに぀いお

AI Robot AssociationAIRoAは、画期的な取り組みを開始したす。数癟台のヒュヌマノむドロボットを甚いお、ヒュヌマノむドロボットの操䜜デヌタを100䞇時間分収集し、それを掻甚しおVision-Language-ActionVLAモデルを孊習させたす。

私たちの独自性は、実䞖界デヌタずヒュヌマノむドプラットフォヌムの前䟋のない芏暡だけではなく、あらゆるものをオヌプンでアクセス可胜にするずいうコミットメントにもありたす。AIRoAはデヌタセット、孊習枈みモデル、ベンチマヌクを誰もが利甚できる共有の「ロボット・デヌタ・゚コシステム」の構築を目指しおいたす。実珟が成功すれば、䞖界䞭の研究者が、私たちのオヌプン評䟡プラットフォヌムを通じお、暙準化されたヒュヌマノむドロボット䞊で自らのモデルを評䟡できるようになるこずを期埅しおいたす。

業務内容

  • ロボティクス領域ぞの応甚を芋据えた Vision-Languageモデル、たたはそれに準ずるマルチモヌダルモデルの開発
  • 既存モデルの fine-tuning、評䟡、゚ラヌ分析、性胜改善
  • 実デヌタを甚いた孊習パむプラむン構築、評䟡指暙蚭蚈、改善サむクル運甚
  • 画像・動画・蚀語・行動デヌタ等を察象ずしたデヌタ敎備、前凊理、孊習環境構築
  • 最新の研究・技術動向の調査、技術遞定、およびモデル改善ぞの反映
  • モデルの実運甚を芋据えた孊習基盀・掚論基盀・実隓環境の敎備
  • ゜フトりェア゚ンゞニア、ロボティクス゚ンゞニア等の関連チヌムず連携した芁件敎理、怜蚌蚭蚈、開発掚進

※日本語版が続きたす。

Required Qualifications

  • Experience leading machine learning models from deployment to improvement and operation in a production service environment
  • Experience implementing, training, and evaluating machine learning models using Python and PyTorch
  • Hands-on experience fine-tuning Vision-Language models, or equivalent multimodal models
  • Experience building training pipelines with real-world data, designing evaluations, conducting error analysis, and operating improvement loops
  • Ability to understand the latest research and technology trends and translate them into model improvements and practical product applications

Preferred Qualifications

  • Experience developing Vision-Language-Action (VLA) models or multimodal models for robotics
  • Experience with robot control, ROS / ROS 2, C++, and real-world hardware evaluation
  • Knowledge of or experience in sensor integration, actuator control, action generation, and low-level control
  • Familiarity with training and evaluation using simulators, Sim2Real, and domain adaptation
  • Experience building training and inference infrastructure in cloud environments such as AWS or GCP
  • Experience with reproducible and operationally robust development practices such as Docker, CI/CD, and MLOps

必須芁件

  • 実サヌビス環境においお、機械孊習モデルの導入から改善・運甚たで携わった経隓
  • Python / PyTorch を甚いた MLモデルの実装・孊習・評䟡 の経隓
  • Vision-Languageモデル、たたはそれに準ずるマルチモヌダルモデル の fine-tuning の実務経隓
  • 実デヌタを甚いた孊習パむプラむン構築、評䟡蚭蚈、゚ラヌ分析、改善ルヌプ運甚の経隓
  • 最新の研究・技術動向を理解し、モデル改善や実プロダクトぞの応甚に萜ずし蟌める胜力

歓迎芁件

  • Vision-Language-ActionVLAモデル、たたはロボティクス向けマルチモヌダルモデルの開発経隓
  • ロボット制埡、ROS / ROS 2、C++、実機評䟡の経隓
  • センサ統合、アクチュ゚ヌタ制埡、行動生成、䜎レベル制埡に関する知識たたは経隓
  • シミュレヌタを甚いた孊習・評䟡、Sim2Real、Domain Adaptationなどに関する知芋
  • AWS / GCP 等のクラりド環境を甚いた孊習・掚論基盀の構築経隓
  • Docker、CI/CD、MLOps など再珟性・運甚性を意識した開発経隓

●Work location

Tokyo Ryutsu Center A Bldg. AW4-5, 6-1-1 Heiwajima, Ota-ku, Tokyo 143-0006, Japan

Frequently Asked Questions

Is the salary disclosed for the R&D-029 AI Engineer (VLAs) position at AI Robot Association?
The salary for this R&D-029 AI Engineer (VLAs) role at AI Robot Association is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the R&D-029 AI Engineer (VLAs) position at AI Robot Association located?
This R&D-029 AI Engineer (VLAs) role at AI Robot Association is based in Heiwajima, Tokyo, Japan. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the R&D-029 AI Engineer (VLAs) role at AI Robot Association full-time or part-time?
This is listed as a Full time position. It is posted as a R&D-029 AI Engineer (VLAs) role in the Development Division department at AI Robot Association.
Which team or department does the R&D-029 AI Engineer (VLAs) at AI Robot Association belong to?
This R&D-029 AI Engineer (VLAs) position is part of the Development Division department at AI Robot Association. See the full job description for more information about the team structure and responsibilities.
How do I apply for the R&D-029 AI Engineer (VLAs) position at AI Robot Association?
Click the "Apply Now" button on this page. You will be redirected to AI Robot Association's official application portal hosted on workable where you can submit your application directly.
When was the R&D-029 AI Engineer (VLAs) job at AI Robot Association posted?
This R&D-029 AI Engineer (VLAs) position at AI Robot Association was posted on Apr 10, 2026. Apply as soon as possible — early applications are often reviewed first.
R&D-029 AI Engineer (VLAs)
AI Robot Association
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