
AI Data Quality Engineer
23 hours ago
The role of an AI Data Quality & Engineering Lead involves leading the development and implementation of high-quality annotation workflows for AI models. This position requires a proactive leader who can drive quality at scale, build and guide a high-performing team, ensure transparency and insight, and champion tool innovation and efficiency.
Key Responsibilities:
- Design and refine quality assurance processes and standard operating procedures.
- Establish comprehensive quality metrics 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.
- Act as the subject matter expert on annotation quality, providing ongoing feedback, training, and support to annotators and project teams.
Requirements:
- At least 3 years of experience in data quality management, data operations, or related roles within AI/ML or data annotation environments.
- A proven track record in designing and executing quality assurance strategies for large-scale, multi-modal data annotation projects.
- Experience managing and developing high-performing, remote or distributed teams.
Qualifications:
- Excellent leadership and communication skills.
- Strong analytical and problem-solving abilities.
- Ability to work collaboratively with cross-functional teams.
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