
AI Data Quality Specialist
6 hours ago
About This Role:
We are seeking a diligent and detail-focused professional to maintain annotation standards and drive continuous improvements in our AI data.
Key Responsibilities:
- Quality Audits: Perform quality audits on annotated datasets to ensure they meet established guidelines and quality benchmarks.
- Statistical Reporting: Leverage metrics such as F1 score and inter-annotator agreement to evaluate data quality.
- Root Cause Analysis: Analyze annotation errors, trends, and project documentation to identify root causes and propose remediation strategies.
Requirements:
- Strong analytical and problem-solving skills with an exceptional eye for detail.
- Excellent written and verbal communication skills to clearly articulate quality issues and collaborate with diverse teams.
- Ability to work independently and manage time effectively to meet deadlines.
- Positive can-do attitude and adaptability to new environments.
Nice to Have:
- Familiarity with data annotation tools (e.g., Labelbox, Dataloop, LabelStudio).
- Experience with multi-modal AI/ML datasets (images, videos, text, audio).
- Knowledge of programming languages (e.g., Python).
What You'll Gain:
- Work remotely from anywhere you're most productive.
- Auditing and analyzing unique datasets across various projects.
- Visible impact on AI model performance through your quality checks and automation ideas.
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