黄寅杰

Key Skills

Software

Don't disclose

Top Subject Matter

AI response quality review and text annotation/classification QA

Image labeling and annotation QA for AI training

Audio transcription QA for AI training

Top Data Types

Text

Image

Audio

Top Task Types

Classification

Transcription

Entity (NER) Classification

Freelancer Overview

Remote AI training contributor for AI response quality review and text evaluation. Core strengths include Don't disclose and Microsoft Excel. Education includes Master's Degree, N/A. AI-training focus includes data types such as Text, Image, and Audio and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Text annotation and labeling assistant (remote AI training)

TextEntity (NER) Classification

Supported text annotation and labeling for language evaluation tasks by categorizing and tagging relevant elements per project schema. Performed QA checks to confirm outputs followed instruction structure and category definitions. Maintained consistent labeling decisions across batches using guideline-based comparison. • Applied label categories and ensured schema adherence • Performed row-level review for obvious labeling errors • Used spreadsheets to track status and results • Ensured repeatable, guideline-consistent decisions

2026 - Present

Remote audio transcription quality assurance contributor

Don't discloseAudioTranscription

Contributed to audio transcription QA by reviewing transcripts for correctness against the source audio. Performed transcription quality checking and flagged obvious issues that violated guidelines. Ensured consistency and accuracy across repeated transcription QA tasks. • Verified transcript accuracy and formatting per instructions • Identified errors or missing content during review • Maintained quality standards across batches • Completed QA checks with detail-oriented consistency

2026 - Present

Entry-level image labeling assistant (remote AI training)

Don't discloseImageClassification

Performed image annotation tasks by labeling relevant categories according to provided guidelines. Supported quality checking by verifying that annotations met instruction requirements and maintained labeling consistency. Identified obvious mistakes and ensured reliable output across repeated annotation work. • Followed detailed visual labeling criteria from project instructions • Checked annotation completeness and category correctness • Maintained consistency across batches • Completed work with accuracy-focused, repetitive task tolerance

2026 - Present

Remote AI training contributor for AI response quality review and text evaluation

Don't discloseText

Conducted AI response evaluation by checking outputs for clarity, helpfulness, factual consistency, tone, and safety alignment with guidelines. Performed text classification QA by comparing model responses against required categories and instruction adherence. Reviewed content quality for obvious errors and guideline violations while maintaining consistency across repeated tasks. • Used English proficiency to read detailed project instructions • Logged and verified results using spreadsheet workflows • Applied quality-check criteria to each response • Communicated findings for alignment with standards

2026 - Present

Education

Work History