Team Lead, Human Data Operations - Vision, Image & Video
New
J
JobgetherAI data operations
Eligible locations include the United States, Dubai, Ireland, United Kingdom, Japan, India, Indonesia, South Korea, the Philippines, and Singapore.Full-TimeLead
Salary not disclosed
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Job Details
- Experience
- At least 1 year of hands-on experience in data labeling, annotation, AI training or evaluation, content quality, or a related operational field. A bachelor’s degree or at least 4 years of relevant professional experience in lieu of a degree.
- Required Skills
- JiraQuality AssuranceNotion
Requirements
- Have at least 1 year of hands-on experience in data labeling, annotation, AI training or evaluation, content quality, or a related operational field.
- Hold a bachelor’s degree or have at least 4 years of relevant professional experience in lieu of a degree.
- Have experience with data quality metrics, annotation workflows, and guideline-driven processes.
- Be familiar with project management and collaboration tools such as Notion, Axiom, JIRA, Linear, or equivalent platforms.
- Have working knowledge of AI and machine learning concepts, particularly how high-quality training data affects model performance.
- Have quality assurance experience in creative, visual, or media-related projects.
- Be able to manage multiple projects, prioritize effectively, and perform in a fast-paced environment.
- Have strong analytical skills and experience using metrics and KPIs to drive operational improvements; SQL knowledge is a plus.
- Bring strong organizational skills, attention to detail, proactive problem-solving, and a continuous-improvement mindset.
- Be able to combine strategic thinking with hands-on execution.
Responsibilities
- Own quality and delivery for assigned human data projects, personally reviewing work for accuracy, consistency, guideline adherence, and quality.
- Lead, coach, and performance-manage a team of AI Tutors through feedback, reviews, action plans, shadow sessions, and development.
- Participate in labeling and review activities to maintain standards and demonstrate best practices.
- Manage guideline adherence, taxonomy processes, quality assurance workflows, and certification standards.
- Identify operational bottlenecks and implement improvements to efficiency, quality, and throughput.
- Track team and project performance using KPIs and dashboards, including quality metrics, throughput, and send-back rates.
- Develop and deliver training materials, practice exercises, and certification benchmarks; oversee certifications and workforce adjustments.
- Partner with Human Data Managers, other Team Leads, and Engineering to turn AI model requirements into labeling strategies and operational guidelines.
- Document project outcomes, risks, and results; recommend process improvements and provide status updates.
- Represent AI Tutors’ needs and perspectives while promoting collaboration across the Human Data organization.
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