- Own tracking and reporting of CV accuracy metrics, per customer and per identifier type.
- Investigate misclassifications and false negatives to categorize root causes and identify patterns.
- Curate, label, and prioritize datasets for model retraining in partnership with ML and CV engineers.
- Build and improve the continuous learning pipeline to facilitate weekly model shipments.
- Define functional acceptance criteria for CV accuracy per customer and track progress.
- Translate accuracy findings into actionable decisions for engineering and customer-facing teams.
- Develop labeling and preprocessing tooling and own technical fixes for identified error patterns.
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