Yang Q.

Key Skills

Software

Don't disclose

Top Subject Matter

LLM output evaluation and code generation review (programming QA)

Text/document annotation and structured data validation

Legal Services & Contract Review

Top Data Types

Text

Document

Top Task Types

Entity (NER) Classification

Freelancer Overview

AI Data Annotation & Model Evaluation - Project-based Experience. Professional background includes roles such as AI Code and QA Reviewer and Software Developer and QA Automation Specialist. Core strengths include Don't disclose. AI-training focus includes data types such as Computer Code, Programming, and Text and labeling workflows including Evaluation, Rating, and Entity (NER) Classification.

Labeling Experience

AI Data Annotation & Model Evaluation - Project-based Experience (text/document & structured validation)

Don't discloseTextEntity (NER) Classification

Performed text/document review with metadata checks, structured-field validation, and duplicate detection to ensure data quality. Applied detailed guidelines across batches of technical tasks and used review evidence to support corrections. Conducted data-quality analysis focused on consistency, completeness, and edge-case handling. • Verified structured fields and metadata for correctness and completeness • Detected duplicates and validated consistency across records • Reviewed document/text inputs for adherence to annotation rules • Used LLM-assisted workflows to find recurring quality issues

Present

AI Data Annotation & Model Evaluation - Project-based Experience

Don't disclose

Reviewed AI-generated programming outputs against task requirements, acceptance criteria, and technical constraints. Identified functional defects, incomplete implementations, inaccurate claims, configuration risks, and weak test coverage. Produced evidence-based issue summaries and re-validated revised outputs through repeat evaluation, command-line testing, and log analysis. • Classified findings by type and severity for correction prioritization • Validated requirement compliance and detected recurring failure patterns across batches • Assisted LLM-assisted QA workflows to ensure consistent guideline adherence • Performed evidence-based quality checks to confirm fixes before delivery

Present

Education

Work History