We are a robotics software startup building an operating system and systems stack that help robots work reliably in human spaces. Our mission is to move robotics beyond lab demos and into practical, field-ready deployments in environments like hospitals, hospitality, and retail. We work at the intersection of software, autonomy, interaction, and operations to make robots useful in the real world.
Our approach is hands-on, fast-moving, and grounded in deployment. We partner with leading robotics platforms and validate solutions in live environments, with a long-term goal of making robots practical, affordable, and widely deployable. We value builders who thrive in early-stage startup settings, move quickly, and care deeply about shipping systems that work in the field.
As a Data Engineer, you will build the data infrastructure that powers AI and autonomous robotics systems. Your work will help turn every sensor reading, robot action, and operational log into reliable, usable data for embodied learning, model training, SLAM improvement, and operational monitoring. This is a hands-on role focused on making data trustworthy and actionable across the robot lifecycle.
You will design and operate real-time and batch pipelines, manage datasets for training and evaluation, and help build the end-to-end embodied learning pipeline. You’ll also work with cloud data warehouses, streaming infrastructure, dashboards, and data quality monitoring, while partnering closely with the AI team on experiment tracking and model evaluation. The role is based in Tokyo with a hybrid setup, and English-speaking candidates are welcome.
3+ years of professional data engineering experience
Strong Python and/or SQL skills for large-scale data processing
Experience with cloud data infrastructure such as GCP, AWS, or Azure
ETL/ELT pipeline design and implementation using tools like Airflow, dbt, or Spark
Data warehouse design experience; robotics, sensor, or streaming data experience is a plus
