QA Data Labeller
1 week ago
About the company
Fast-track your career with the Marlee Talent Pool. We're not just matching you with your ideal roles but unlocking your long-term career potential. Marlee goes above and beyond by identifying key strengths for your CV, helping you discover a career direction you might not have considered where you can truly thrive, and guiding you to develop those essential soft human skills that close gaps in your resume.
Marlee's innovative approach then places you in teams where you'll flourish. Using cutting-edge motivational science, we connect you with roles in teams and within organizations that make your heart sing and help our partners build their dream teams.
About the role
In this dynamic position, you'll be at the heart of our partner's AI initiatives, ensuring the accuracy and quality of data labeling operations. You'll work within their Generative AI Platform Group, collaborating with a dedicated team of 18 contractors and an in-house lead.
Your responsibilities will include:
- Bringing precision to data labeling by annotating and generating text, elements, and design templates while adhering to established guidelines
- Conducting thorough quality checks on both internal labellers and contractors' work to maintain exceptional standards
- Supporting contractor lifecycle management, from hiring through onboarding
- Building and maintaining a deep understanding of quality label standards
- Monitoring quality trends and sharing insights with key stakeholders
- Contributing to the enhancement of labeling processes, guidelines, and tools alongside the team leads
What our partner is looking for:
- 3+ years of hands-on experience in Data Labeling and/or Data Annotation
- A creative eye, demonstrated through multimedia design experience and a strong portfolio
- Natural attention to detail and organizational abilities
- Adaptability and eagerness to learn in a growing environment
- Collaborative spirit with basic operational and people management experience
- Foundational knowledge of data annotation principles
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