نصائح م.

Key Skills

Software

Other

Top Subject Matter

Arabic language quality assurance and AI output evaluation

Arabic prompt engineering and response optimization for AI training

Arabic content creation with quality checks relevant to AI training data

Top Data Types

Text

Top Task Types

Prompt + Response Writing (SFT)

Text Generation

Freelancer Overview

Arabic AI Content Quality & Evaluation (AI training simulations). Enthusiastic early-stage Artificial Intelligence undergraduate student building hands-on experience across complex digital workflows, language research, and quality-focused execution. Core strengths include language auditing, structured data evaluation, and creative writing. Education includes pursuing a Bachelor of Science at Arab Open University, alongside being a Certified Freelancer through Freelancer & BrightDock. AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Prompt + Response Writing (SFT).

Labeling Experience

Independent Arabic AI/Content Generation & Quality Control

OtherTextText Generation

Formulated creative copy, micro-narratives, and educational materials in structured Arabic. Managed independent content production from ideation to final delivery with strict quality control. Applied linguistic and logical quality checks to ensure clarity and consistency in generated materials. • Produced structured Arabic text content designed for audience comprehension. • Ensured accuracy, coherence, and logical flow through self-review. • Managed the full creation lifecycle from concept to final output. • Applied attention to language quality for culturally relevant presentation.

Present

Prompt Engineering & Response Optimization

OtherTextPrompt + Response Writing (SFT)

Designed and tested structured prompting workflows to improve the quality of generative Arabic text outputs. Conducted iterative prompt refinement to steer models toward natural, human-like Arabic expression. Analyzed edge cases where models struggled with complex Arabic metaphors or structural derivations. • Built prompt workflows and tested output quality changes across iterations. • Refined prompts using feedback loops to improve fluency and naturalness. • Investigated failure modes related to metaphor comprehension and grammar/structure. • Calibrated prompt instructions to better control Arabic linguistic outcomes.

Present

Arabic AI Content Quality & Evaluation (AI training simulations)

OtherText

Audited and evaluated AI-generated Arabic text for linguistic quality, grammatical accuracy, and contextual fluency. Identified factual contradictions and logical gaps within model outputs to improve training simulations. Tuned localized data parameters so responses matched Middle Eastern cultural nuances. • Reviewed Arabic outputs for grammar, meaning consistency, and contextual appropriateness. • Flagged subtle contradiction patterns and reasoning breakdowns during evaluation. • Assessed cultural relevance and logical flow of generated responses. • Supported iterative improvement by documenting issues for refinement.

Present

Education

Work History