Data Infrastructure Engineer

What you'll do

• Build ingestion, distributed processing, and data-quality and curation systems for large-scale sensor and demonstration data.
• Contribute to multimodal data storage, retrieval, format, versioning, and lineage design.
• Debug production pipelines and collaborate with modeling and research partners on data needs.

What they ask for

• 2+ years of software engineering experience, with some exposure to data pipelines, data engineering, or backend systems.
• Strong Python programming fundamentals and ability to write performant, production-grade data processing code.
• Experience with at least one distributed data processing framework, or strong fundamentals and willingness to ramp up quickly.
• Familiarity with object storage, data lake table formats, and warehouse-versus-lake tradeoffs.

Nice to have

• Experience with workflow orchestration tools, streaming ingestion, or automated data quality and curation systems.
• Experience with robotics- or embodied-AI-specific data.

Tools

Python, Spark, Ray, Dask, Flink, Airflow, Dagster, Prefect

AI focus

Supports Physical AI by preparing robot sensor and human demonstration data for model training; data curation may include auto-labeling and ML models in annotation or filtering pipelines.