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Confirmed on the employer's own hiring board on Oct 26, 2026. First seen by Alion on Jul 30, 2026. AI Robot Association scores C on the Alion truth index.

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AI Robot Association, known as AIRoA, is a Japanese non-profit organization that advances AI-powered robotics through open data platforms and collaborative research. It develops robot data ecosystems, foundation models and shared software tools to speed up the deployment of humanoid and general-purpose robots, and hires corporate IT, governance and administration staff. The association is headquartered in Ōta, Tokyo, Japan.

※日本語版が続きます。

About AIRoA

AI Robot Association (AIRoA) is an organization dedicated to collecting large-scale real-world robot data, including data from humanoid robots, and advancing the development of generative AI foundation models in the field of robotics.

AIRoA has been selected by Japan’s Ministry of Economy, Trade and Industry (METI) and NEDO as an implementing organization for the development of a data platform for generative AI foundation models in robotics under the “Post-5G Information and Communication Systems Infrastructure Enhancement R&D Project.” The project budget is JPY 20.5 billion.

Based on this foundation, AIRoA is working on 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 by leveraging this data.

Role Overview

This position is responsible for designing, implementing, and tuning low-level control systems that translate motion commands generated by higher-level control layers into precise and reliable torque and motion for the joint actuators of humanoid and dual-arm robots.

You will work primarily at the layer closest to motor control, including field-oriented control (FOC) for brushless

motors; current, torque, velocity, and position control loops; motor-control-board bring-up; sensor calibration; and implementation of safety mechanisms.

Rather than high-level (meta) control such as Motion Planning or Navigation, you will take end-to-end ownership of actuator-level control firmware, from prototype through mass production. This role supports the lowest layer of the control stack and serves as the bridge that ensures the motions required by the Whole-Body Control and AI/ML teams are realized reliably on physical hardware.

Responsibilitie

  • Design, implement, and tune FOC (vector control) for brushless actuators, current and torque control loops based on dq transformation, and velocity and position control loops.
  • Bring up and debug custom motor-control boards and sensors.
  • Build calibration and synchronization pipelines for encoders and current/voltage measurements.
  • Implement actuator safety mechanisms, including overcurrent, overtemperature, watchdog, and brownout protection.
  • Design control loops under real-time constraints using low-level peripherals such as timers, ADC, PWM, and DMA.
  • Implement communication interfaces such as CAN (FD) and EtherCAT, and design interfaces with higher-level software platforms.
  • Develop diagnostic and logging mechanisms for torque, current, temperature, error states, and other signals to support fault detection during operation on physical hardware.
  • Collaborate with the Whole-Body Control and AI/ML teams on force and compliance control under dynamic loads.
  • Continuously improve control performance through on-hardware validation and parameter tuning.

AIRoAについて

AI Robot Association(AIRoA)は、ヒューマノイドロボットをはじめとする実世界ロボットの⼤規模データを収集し、ロボティクス分野における⽣成AI基盤モデルの開発を推進する組織です。

AIRoAは、経済産業省およびNEDOの「ポスト5G情報通信システム基盤強化研究開発事業」において、ロボティクス分野の⽣成AI基盤モデル開発に向けたデータプラットフォーム開発の採択事業者に決定しており、事業予算は205億円です。この基盤をもとに、100台以上のロボットを⽤いて100万時間規模のヒューマノイドロボット操作データを収集し、それを活⽤して世界最⾼⽔準のVision-Language-Action(VLA)モデルを開発するプロジェクトを進めています。

募集概要

本ポジションは、ヒューマノイドや双腕ロボットの関節アクチュエータについて、上位の制御層が⽣成する動作指令を、精密かつ信頼性の⾼いトルク‧動作へと変換する低レベル制御システムの設計‧実装‧チューニングを担うポジションです。ブラシレスモータのベクトル制御(FOC)や電流‧トルク‧速度‧位置の各制御ループ、モータ制御基板のブリングアップ、センサ校正、安全機構の実装など、モータ制御に最も近いレイヤを中⼼的に担当していただきます。

Motion PlanningやNavigationといった⾼レベル(メタ)な制御ではなく、その⼟台となるアクチュエータレベルの制御ファームウェアを、プロトタイプから量産まで⼀貫してオーナーシップを持って開発します。全⾝制御(Whole-Body Control)チームやAI∕MLチームが求める動作を、実機のハードウェア上で確実に実現するための橋渡しを担う、制御スタックの最下層を⽀える役割です。

業務内容

  • ブラシレスアクチュエータ向けのFOC(ベクトル制御)、dq変換に基づく電流‧トルク制御ループ、および速度‧位置制御ループの設計‧実装‧チューニング
  • カスタムモータ制御基板およびセンサのブリングアップとデバッグ
  • エンコーダ、電流∕電圧計測のキャリブレーション‧同期パイプラインの構築
  • 過電流‧過熱‧ウォッチドッグ‧ブラウンアウト保護など、アクチュエータの安全機構の実装
  • タイマ∕ADC∕PWM∕DMA等の低レベルペリフェラルを活⽤した、リアルタイム制約下での制御ループ設計
  • CANFD、EtherCAT等の通信インターフェースの実装と、上位ソフトウェア基盤とのインターフェース設計
  • 実機運⽤時の故障検出に向けた、トルク‧電流‧温度‧エラー状態などの診断‧ロギング機構の開発
  • 動的負荷下での⼒‧コンプライアンス制御に向けた、全⾝制御‧AI∕MLチームとの協働
  • 実機での動作検証‧パラメータチューニングによる制御性能の継続的な改善

Requirements

※日本語版が続きます。

Required Qualifications

  • Professional experience with at least one of the following: robotic arms, robotic hands, or humanoid robots.
  • At least 3 years of professional experience in real-time embedded software development, including microcontrollers, device drivers, and low-level libraries.
  • Strong proficiency in C/C++, with experience implementing low-level peripherals such as timers, ADC, PWM, DMA, and non-volatile memory.
  • Practical knowledge of motor-control theory, including FOC/vector control and dq transformation, and experience designing and implementing current, torque, velocity, and position control loops.
  • Experience working with encoders and current/voltage sensors, including calibration and synchronization.
  • Experience implementing or debugging physical hardware using communication interfaces such as SPI, UART, CAN (FD), RS-485, and EtherCAT.
  • Experience implementing actuator safety mechanisms such as overcurrent, overtemperature, watchdog, and brownout protection.
  • Business level Japanese

Preferred Qualifications

  • Experience developing and shipping motor-control firmware from prototype through mass production.
  • Experience with brushless DC motors, servo motors, and actuator control.
  • Understanding of RTOS concepts and hands-on implementation experience.
  • Experience with motion control using EtherCAT, CANopen, CiA 402, or similar technologies.
  • Knowledge of real-time control, control-cycle design, latency reduction, and jitter reduction.
  • Experience coordinating with the Whole-Body Control layer for torque control, impedance control, admittance control, or similar methods.
  • Experience using Python or similar tools for log analysis, validation automation, and test-tool development.
  • Experience designing and validating control models using MATLAB/Simulink or similar tools.
  • Experience using physics simulators such as MuJoCo, Isaac, or Pinocchio.
  • Ability to read technical documentation in English and experience communicating technically with overseas vendors.

必須要件

  • ロボットアーム、ハンド、ヒューマノイドいずれかの実務経験
  • リアルタイム組み込みソフトウェア開発の実務経験3年以上(マイコン、デバイスドライバ、低レベルライブラリの実装)
  • C / C の⾼い習熟と、タイマ∕ADC∕PWM∕DMA∕不揮発メモリ等の低レベルペリフェラルの実装経験
  • モータ制御理論(FOC∕ベクトル制御、dq変換)の実践的知識と、電流‧トルク‧速度‧位置制御ループの設計‧実装経験
  • エンコーダおよび電流∕電圧センサの扱い(キャリブレーション‧同期を含む)の経験
  • SPI、UART、CANFD、RS485、EtherCAT等の通信インターフェースを⽤いた実装または実機デバッグ経験
  • 過電流‧過熱‧ウォッチドッグ‧ブラウンアウト保護など、アクチュエータの安全機構の実装経験
  • ビジネスレベルの日本語能力

歓迎要件

  • プロトタイプから量産までのモータ制御ファームウェアの開発‧出荷経験
  • ブラシレスDCモータ、サーボモータ、アクチュエータ制御の経験
  • RTOSの概念理解および実装経験
  • EtherCAT、CANopen、CiA 402等を⽤いたモーション制御経験
  • リアルタイム制御、制御周期設計、レイテンシ削減‧ジッタ低減に関する知識
  • トルク制御‧インピーダンス∕アドミッタンス制御など、全⾝制御(Whole-Body Control)レイヤとの協調制御の経験
  • Python等を⽤いたログ解析、検証⾃動化、テストツール開発の経験
  • MATLAB / Simulink等を⽤いた制御モデルの設計‧検証経験
  • MuJoCo、Isaac、Pinocchio等の物理シミュレータの使⽤経験
  • 英語での技術ドキュメント読解、海外ベンダーとの技術コミュニケーション経験

Benefits

※日本語版が続きます。

Few initiatives globally match the scale of this project in collecting large-scale robotic data and developing foundation models for embodied AI. As part of one of Japan’s leading national programs, the project is supported by a 20.5 billion yen investment from NEDO.

This role will be central to the project’s success. You will have significant ownership and technical autonomy, with the opportunity to shape core systems that define the future of large-scale robotics and embodied AI.

Engineers are strongly encouraged to grow their careers through this initiative-for example, by leading system deployments, contributing to open-source robotics software, and driving engineering excellence across large-scale robotic platforms.

このプロジェクトは、大規模なロボットデータ収集と embodied AI 向け基盤モデルの開発という点において、世界的に見ても類を見ない規模を誇ります。日本を代表する国家プロジェクトの一つとして、NEDO による 205 億円の投資支援を受けています。

このポジションは、プロジェクト成功の中核を担う役割です。大きなオーナーシップと技術的裁量を持ち、大規模ロボティクスおよび embodied AI の未来を形づくる中核システムの設計・構築に深く関わることができます。

また、本イニシアチブを通じてエンジニアとしてのキャリアを大きく伸ばすことが強く期待されています。たとえば、システム展開の主導、オープンソースのロボティクスソフトウェアへの貢献、大規模ロボットプラットフォーム全体にわたるエンジニアリング品質の向上推進などに取り組む機会があります。

•Work location

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

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