Description

You will own data quality across 10+ ML labeling pipelines, identifying systemic flaws and driving improvements that directly impact model accuracy and safety. Collaborate with engineering and operations to ensure autonomous driving training data meets the highest standards.

Requirements

• Precision-minded with ability to distinguish labeling errors from system errors
• Experience with data labeling pipelines and quality metrics
• Ability to operate above execution layer and provide quality diagnostic lens
• Strategic thinking to connect labeling quality to model performance and safety

Responsibilities

• Own data quality standard across 10+ labeling pipelines
• Identify and close quality gaps by auditing workflows and tracing root causes
• Design scalable processes to improve labeling accuracy and reduce systematic errors
• Serve as strategic interface between Autonomy Engineering and ML Operations