Role: Data Labelers
Location: India (Fully Remote)
Work Hours: Standard 1st Shift
We are seeking detail-oriented Data Labeling & Validation Specialists to support OCR and Intelligent Document Processing (IDP) systems.
This role combines hands-on document annotation with structured validation of automated labeling outputs. You will play a key role in the human-in-the-loop pipeline, ensuring machine learning models are trained on high-quality, accurate ground truth data.
Success in this role requires prior hands-on annotation experience and the ability to evaluate whether automated outputs meet quality expectations, identify error patterns, and provide structured feedback to improve model performance.
Key Responsibilities
Document Annotation
- Annotate semi-structured and unstructured documents across diverse formats and domains
- Perform labeling across key IDP elements, including:
- Text recognition (including handwriting)
- Document classification
- Field extraction (PII, dates, amounts, signatures, etc.)
- Table detection and structure
- Label document layout elements such as zones, reading order, and hierarchy
- Verify OCR output accuracy and correct recognition errors
- Handle complex or ambiguous document formats beyond automated capabilities
- Maintain high levels of accuracy and consistency across all annotation tasks
Auto-Label Validation & Error Analysis
- Review sampled subsets of auto-labeled outputs and validate against ground truth
- Identify, categorize, and document errors—including distinguishing:
- Isolated issues
- Systematic failure patterns across document types
- Provide structured, actionable feedback to ML engineering teams
- Assess confidence scores and flag outputs below quality thresholds
- Track validation metrics over time and identify quality trends
Quality Assurance & Feedback
- Review annotations completed by other team members to ensure consistency
- Identify and document edge cases (e.g., unusual layouts, ambiguous fields)
- Participate in calibration sessions to align on annotation standards
- Provide feedback to improve annotation guidelines and workflows
- Adhere strictly to data privacy and confidentiality standards
Required Qualifications:
Education & Experience
- High school diploma or equivalent; Associate's or Bachelor's degree preferred
- 1+ year of hands-on experience in document annotation or data labeling (direct annotation required)
- Proven ability to maintain high accuracy in repetitive, detail-oriented tasks
- Experience working with and following annotation guidelines
Technical Skills
- Familiarity with annotation tools and labeling platforms
- Understanding of document structure and layout types
- Basic knowledge of data privacy and security practices
- Reliable computer and high-speed internet connection
- Strong English reading comprehension and written communication skills
Analytical Skills
- Ability to distinguish between isolated errors and systematic issues
- Strong pattern recognition across large datasets
- Critical thinking to evaluate ambiguous cases and escalate appropriately
- High attention to detail when reviewing auto-generated outputs
Preferred
- 1–2 years of experience in OCR, IDP, or document labeling workflows
- Experience with auto-labeling systems or AI-assisted annotation tools
- Background reviewing or auditing machine-generated outputs
- Familiarity with inter-annotator agreement and data quality metrics
- Domain expertise in document-heavy industries (e.g., finance, legal, healthcare)
- Proficiency in languages beyond English
- Experience with spreadsheets, data tracking, or reporting tool
