Data Labeling Expert - Remote
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About the Role
Location: Remote Job Type: Contract Role Description Join a dynamic and fast-growing AI infrastructure company that collaborates with Fortune 100 clients to shape the future of machine learning and artificial intelligence.
Key Skills for This Role
Full Job Posting
Description
- Join a dynamic and fast-growing AI infrastructure company that collaborates with Fortune 100 clients to shape the future of machine learning and artificial intelligence.
- As a Data Annotator, you will be responsible for accurately identifying, classifying, and annotating entities within PDF documents.
- Your work will directly contribute to training AI models that extract structured information from complex documents, making high-quality annotation critical to project success.
- Your Profile
- Bachelor’s degree (any field; preference for Technology, Engineering, or Data-related disciplines).
- 6 months - 2+ years of experience in data annotation, labeling, or similar roles (preferred but not mandatory).
- Strong attention to detail and ability to follow complex annotation guidelines.
- Basic understanding of document structures (text blocks, tables, forms, figures, etc.).
- Ability to interpret and apply rules related to bounding boxes, classification, and reading order
- Comfortable working with repetitive tasks while maintaining high accuracy.
- Familiarity with annotation tools or platforms is a plus.
Key Responsibilities
- Annotate PDF documents by drawing precise bounding boxes around entities such as text, tables, figures, captions, headers, and key-value structures.
- Classify annotated elements according to project guidelines.
- Ensure bounding boxes are tight, accurate, and follow annotation standards.
- Maintain correct reading order and logical structure across document elements.
- Handle complex layouts including multi-column text, forms, tables, and rotated pages.
- Follow detailed annotation instructions and apply rules consistently across all tasks.
- Identify and flag unclear cases or guideline gaps to supervisors.
- Maintain confidentiality and adhere strictly to data security policies.
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