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Salary
$29k – $72k per year (Estimated)
Location
Remote (Japan)
Seniority
Middle · 3+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Omakase Robotics, a division of Zeals, is building Omakase OS, a software and systems stack that makes robots practical and reliable in human environments. We combine software, hardware, autonomy, and operations to deploy robots in real-world settings like hospitals, hospitality, and retail.

About Omakase Robotics

Omakase Robotics is building Omakase OS - a software and systems stack that turns robots into reliable workers for human spaces.

We started from software, but quickly learned that software alone is not enough for real-world deployment. Making robots useful in hospitals, hospitality, and retail requires hardware, autonomy, interaction, and operations designed together. Our focus is not lab demos - it's robots that work in the field.

We partner with leading platforms including Unitree and are actively validating robots in real environments such as hospitals. Our long-term goal: make robots practical, affordable, and widely deployable.

About this Role

As a Data Engineer at Omakase Robotics, you will build the data infrastructure that feeds our AI and autonomous systems. Every sensor reading, robot action, and field operation generates valuable data - you will make that data reliable, usable, and impactful for VLA model training, SLAM improvement, and operational monitoring. Unlike competitors building warehouse fleet dashboards, your primary charter is the ELA (Embodied Learning from Action) pipeline - training data that makes our robots smarter in the real world.

What You'll Do

  • Build real-time and batch data collection pipelines for robot sensor data and operational logs
  • Design and manage training datasets for VLA models and SLAM systems (preprocessing, versioning, quality control)
  • Design and implement the ELA (Embodied Learning from Action) pipeline end-to-end
  • Architect and operate cloud data warehouses (BigQuery, Snowflake, Redshift, or equivalent)
  • Build robot fleet monitoring dashboards and operational reporting (Grafana, Looker, etc.)
  • Partner with the AI team on experiment tracking and model evaluation infrastructure (MLflow, Kubeflow)
  • Automate data quality monitoring and alerting
  • Build real-time streaming infrastructure (Kafka, Pub/Sub) for live robot telemetry

Required Qualifications

  • 3+ years of data engineering experience in a professional setting
  • Strong Python and/or SQL skills for large-scale data processing
  • Experience building and operating cloud data infrastructure (GCP, AWS, or Azure)
  • ETL/ELT pipeline design and implementation (Airflow, dbt, Spark, or equivalent)
  • Data warehouse design experience

Nice to Have

  • Experience processing robotics, autonomous systems, or sensor data
  • MLOps experience (MLflow, Kubeflow, Weights & Biases)
  • Real-time streaming experience (Kafka, Pub/Sub)
  • Familiarity with multithreading and data-sharing patterns (circular buffers, channels, locks)
  • English-only candidates welcome - Japanese not required for this role

Who Will Thrive Here

  • Thrive in an early-stage startup where you help define how things work
  • Want direct, hands-on access to real robots - a level of freedom rare at larger companies
  • Move fast, iterate quickly, and care about shipping things that work in the field
  • Excited about Japan's first robotics OS platform and its real-world deployments (hospital, Tsukuba PoC)

Omakase Roboticsについて

Omakase Roboticsは、ロボットを人の生活空間で実際に働かせるためのソフトウェア・システム基盤「Omakase OS」を開発しています。

私たちは当初ソフトウェアからスタートしましたが、実環境でのデプロイにはソフトウェアだけでは不十分と学びました。病院・ホテル・小売などの環境でロボットを実用化するには、ハードウェア・自律ナビゲーション・HRI・運用を一体として設計する必要があります。

私たちの目標は、研究室のデモで終わるロボットではなく、実際の現場で稼働するロボットをつくることです。

現在、Unitreeなどのロボットプラットフォームと連携し、病院などの実環境での検証を進めており、長期的には、ロボットを社会で広く・実用的に低コストで展開することを目指しています。

このポジションについて

Omakase Roboticsでは、Vision-Language-Action(VLA)モデルを活用したEmbodied AIの開発を進めています。

Data Engineerは、ロボットから得られる実世界データを高品質な学習データへと変換するための、データ収集基盤の構築・運用を担います。従来のETLや分析基盤を構築するData Engineerとは異なり、Robotics・AI・Field Deploymentチームと連携しながら、データ収集・品質管理・データセット管理を通じてEmbodied AIの継続的な改善を支えるポジションです。

主な業務内容

  • VLAモデル学習向けロボティクスデータ収集基盤の構築・運用
  • カメラ、LiDAR、IMU、ロボットテレメトリーなどのマルチモーダルデータセットの設計・管理
  • データ品質管理、バリデーション、データセットバージョニングの仕組みの構築
  • Robotics・AI・Field Deploymentチームと連携したデータ収集プロセスの改善
  • ロボットテレメトリー、実験管理、およびEmbodied AI向けデータ基盤の運用支援

必須要件

  • Robotics、Embodied AI、または機械学習分野におけるデータ基盤構築の実務経験(3年以上)
  • ロボティクス向けデータ収集基盤、またはRobot Learningワークフローの構築・運用経験
  • カメラ、LiDAR、IMUなどのマルチモーダルセンサーデータの取り扱い経験
  • Pythonによる開発経験
  • Vision-Language-Action(VLA)、Robot Learning、SLAMなどのロボティクス技術に関する知識

歓迎スキル

  • ROS / ROS2の利用経験
  • LeRobot、MCAP、RLDSなどのロボティクス向けデータフォーマットの利用経験
  • Teleoperationやロボットデータ収集オペレーションの経験
  • MLflow、Weights & BiasesなどのExperiment Trackingツールの利用経験

こんな方と働きたい

  • 立ち上げフェーズをともに楽しめる方
  • 実際にロボットに直接触れられる環境を求めている方(大企業や上場企業では得難い自由度があります)
  • ハードワークを厭わず、スピード感を持って動ける方
  • 現場での課題解決を楽しめる方
  • つくば大学PoC・病院検証など、すでに始まっている実環境でのロボット導入・運用に携わりたい方
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