Causal Labs
Member of Technical Staff — Data Ingestion & Quality
San Francisco +1 · On-site · Staff · Full-time · Posted Jul 19, 2026
- Location
- San Francisco
Singapore
About the job
Owns physical-world datasets end to end, sourcing and accessing data, building ingestion pipelines, and ensuring it is standardized and high quality for model training.
What you'll do
- Research and source multimodal physical data, securing access through partners, vendors, and public archives.
- Build and operate batch and streaming data pipelines, including orchestration, storage, and monitoring.
- Develop and own data-quality metrics and automated checks, and work with researchers and vendors to improve datasets.
What they ask for
- Demonstrated experience building large-scale data pipelines, QA systems, or evaluation workflows.
- Ability to identify subtle data inconsistencies and understand their potential effect on model performance.
- Ability to learn unfamiliar source material, including specifications, sensor documentation, and vendor manuals.
- Experience working with external data vendors and partners, and driving deliverables end to end.
Tools
Apache Spark, Spark, Ray, Beam
AI focus
Supports training and evaluation of a Large Physics foundation Model by sourcing and preparing physical-world data and validating dataset improvements with researchers.
Model-written summary · the original posting is authoritative