Shehab S.

Key Skills

Software

Data Annotation Tech

Top Subject Matter

Arabic LLM response evaluation

RLHF preference ranking

reward model optimization

Top Data Types

Text

Document

Top Task Types

RLHF

Freelancer Overview

AI Data Trainer (Arabic Specialist) – DataAnnotation.tech. Core strengths include Data Annotation Tech and Alignerr. Education includes Bachelor of Medicine, Bachelor of Surgery, Al-Azhar University. AI-training focus includes data types such as Text and labeling workflows including RLHF, Evaluation, and Rating.

Labeling Experience

AI Data Trainer (Arabic Specialist) – DataAnnotation.tech

Data Annotation TechTextRLHF

Evaluate and rank Arabic LLM responses for quality, factual accuracy, and safety compliance in Arabic language contexts. Conduct structured RLHF comparisons to optimize reward models and improve personalization fidelity aligned with defined user personas. Identify edge cases and contribute to annotation guideline refinement for large-scale Arabic response evaluation. • Reward-model-oriented preference comparisons for Arabic outputs • Fact-checking and claim verification across diverse domains • Safety compliance and hallucination detection focused evaluation • Persona and personalization alignment annotation support

2025 - Present

AI Content Evaluator – Alignerr & Labelbox

Text

Labeled and classified large-scale Arabic NLP datasets using structured taxonomies. Executed side-by-side model ranking to support reward model training and improve response selection quality. Applied intent categorization and NER tagging while maintaining high inter-annotator consistency across multilingual tasks. • Arabic dataset labeling with intent and NER classification • Side-by-side response/model ranking for reward model training • Taxonomy-driven label application for structured annotation • Quality control via inter-annotator consistency practices

2024 - 2025

Education

Work History