Build a highly-scalable data platform at a stealth-mode AI lab: ingest and process hundreds of terabytes of ML training data, define data-quality metrics, and architect validation/integrity mechanisms for state-of-the-art ML models. Core stack: Python back-end microservices and ETL pipelines on cloud (AWS/GCP/Azure) with Docker and Terraform.
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