About Karen
I deliver high-precision dataset annotation, labeling, and quality validation to help AI teams train robust machine learning models. In the AI industry, data quality is the single most critical factor for model success. I ensure your training data is clean, consistent, and deployment-ready, preventing costly retraining cycles.
English
Native or bilingual
Remote only
Primarily works remotely
Experience
- MoerlingAI data notation analystApril 2025 - April 2026 (1 year)Transcption : converted audio/ video recordings into text to train speech to text models.Data Cleaning: Cleaned, structured and organied raw data to make it usable for ML models.Qulity Control: Reviewed and crrected annotations made by peers or automated tools
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