Data Engineer

 

 

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 with robotics learning data formats (LeRobot, mcap, RLDS)
• 　　Experience with time-synchronization of multi-modal sensor streams
• 　　Distributed training infrastructure (multi-GPU, multi-node)
• 　　Automated evaluation pipelines (open-loop MSE, success rate benchmarks)
• 　　GPU cluster operations (job scheduling, cost management)
• 　　MLflow, Weights & Biases, or similar experiment tracking

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)