Fang E.

Key Skills

Software

Mercor

Top Subject Matter

AI/LLM evaluation for RLHF training

Text classification and information extraction

Search quality evaluation for retrieval/model tuning

Top Data Types

Text

Image

Document

Top Task Types

RLHF

Object Detection

Freelancer Overview

AI Response Evaluation (RLHF) Annotator. Brings 6 months of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Mercor. Education includes Bachelor of Science, Adeleke University. AI-training focus includes data types such as Text and Image and labeling workflows including RLHF, Entity (NER), and Evaluation.

Labeling Experience

Image Tagging & Bounding Boxes Annotator

MercorImageObject Detection

Annotated images using object detection approaches including multi-class labeling and occlusion handling. Produced bounding box style labels while adhering to project-specific taxonomies and dataset requirements. Followed labeling guidelines carefully to preserve consistency across high-volume image tasks. • Object detection bounding boxes • Multi-class labeling • Occlusion handling • Taxonomy/guideline adherence

2023 - Present

Search Quality Rating Annotator

MercorText

Conducted search quality rating using E-E-A-T frameworks and task-specific relevance rubrics. Evaluated Page Quality and Needs Met ratings while considering YMYL content constraints and user intent categories. Ensured ratings were consistent with guideline compliance and calibration requirements. • E-E-A-T based page quality scoring • Needs Met and relevance judgments • YMYL-aware evaluation • User intent (Do/Know/Go) interpretation

2023 - Present

Text Labeling & Classification Annotator

MercorText

Labeled and classified text for multiple NLP tasks including sentiment analysis, intent classification, NER, topic categorization, and toxicity detection. Applied consistent annotation standards to produce high-accuracy labels aligned with training objectives. Interpreted task-specific instructions and label guides throughout repeated labeling sessions. • Sentiment and intent classification • Named entity recognition (NER) • Topic categorization • Toxicity detection and labeling

2023 - Present

AI Response Evaluation (RLHF) Annotator

MercorTextRLHF

Performed AI response evaluation by rating and comparing model outputs across helpfulness, accuracy, instruction-following, safety, and tone dimensions. Completed both single-response rating and A/B comparative judgment tasks following project rubrics and guideline requirements. Maintained calibration across high-volume sessions to support consistent model improvement. • Helpfulness and accuracy scoring • Instruction-following and safety/tone checks • A/B comparative evaluations • Ongoing guideline compliance

2023 - Present

Education

Work History