
Data Quality Leadership Position
23 hours ago
As AI systems expand across industries, the integrity and accuracy of testing, training, and evaluation data have never been more crucial. We need a proactive leader who can architect and uphold high-quality annotation workflows so that AI models are built and evaluated on reliable data without compromising speed or efficiency.
The successful candidate will lead and mentor a team of Data Quality Analysts, setting clear quality goals, delivering feedback, and fostering a culture of precision and accountability. They will ensure quality at scale by developing and continually refining robust QA processes, SOPs, and statistical quality metrics (e.g., F1 score, inter-annotator agreement) to protect the integrity of annotation outputs.
Key responsibilities include:
- Develop and refine quality assurance processes and standard operating procedures to guarantee high-quality outputs.
- Establish comprehensive quality metrics (e.g. F1 score, inter-annotator agreement) that align with business objectives and industry standards.
- Continuously review and refine annotation workflows to proactively identify risks and areas to increase efficiency and reduce errors.
The ideal candidate will have 3+ years of experience in data quality management, data operations, or related roles within AI/ML or data annotation environments. They will have a proven track record in designing and executing quality assurance strategies for large-scale, multi-modal data annotation projects and will be able to lead and develop high-performing teams.
BenefitsThis role offers a unique opportunity to work with cutting-edge technology and make a significant impact on the development of AI models.
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