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Data Labeling Expert - Remote

YO IT Consulting
Department:Data Analysis
Type:REMOTE
Region:Australia
Location:Melbourne, Victoria, Australia
Experience:Entry level
Estimated Salary:A$45,000 - A$65,000
Skills:
DATA ANNOTATIONLABELINGDOCUMENT STRUCTUREATTENTION TO DETAILANNOTATION TOOLS
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Job Description

Posted on: May 6, 2026

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. 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.
Originally posted on LinkedIn

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