
AI Data Assurance Specialist
3 days ago
The role of the AI Data Quality Lead is to design and implement high-quality data annotation workflows, ensuring that AI models are trained on reliable data without compromising speed or efficiency.
Key Responsibilities:
- Develop and refine quality assurance processes and standard operating procedures to guarantee high-quality outputs.
- Establish comprehensive metrics (e.g. F1 score, inter-annotator agreement) aligned with business objectives and industry standards.
- Continuously review and refine annotation workflows to proactively identify risks and areas for improvement.
- Act as the subject matter expert on annotation quality, providing feedback, training, and support to annotators and project teams.
Requirements:
- 3+ years of experience in data quality management, data operations, or related roles within AI/ML environments.
- Proven track record in designing and executing quality assurance strategies for large-scale data annotation projects.
- Leadership experience managing high-performing teams.
- Deep understanding of data annotation processes, quality assurance methodologies, and statistical metrics.
- Strong data-analysis skills.
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