Qusay Ibrahim

Key Skills

Software

Appen

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Text

Top Task Types

Data Collection

Text Generation

Translation Localization

Freelancer Overview

I am an AI training contributor with hands-on experience in data labeling, linguistic quality assurance, and prompt evaluation for large language models (LLMs). I’ve worked on Arabic NLP projects through platforms like Appen and Crowdgen, where I supported LLM fine-tuning and evaluation by generating, reviewing, and refining Arabic prompts and completions to enhance model performance and relevance. With a strong background in microfinance and customer service, I bring industry insight that supports accurate data annotation in financial and business-related contexts. My bilingual proficiency (Arabic-English), attention to detail, and ability to adapt quickly to project guidelines make me a valuable asset in multilingual AI training environments.

Labeling Experience

Arabic Prompt Evaluation and Text Generation – Crowdgen (Fireweed Project)

AppenTextQuestion AnsweringText Generation

Contributed to a large-scale LLM alignment and fine-tuning project focusing on Arabic. Tasks included evaluating AI-generated responses for relevance and accuracy, rewriting low-quality completions, and generating high-quality prompts and answers in both Modern Standard Arabic and Levantine dialect. Ensured adherence to quality guidelines, cultural appropriateness, and linguistic correctness. Provided structured feedback to support reinforcement learning from human feedback (RLHF). Worked with thousands of samples under tight deadlines while maintaining high QA scores.

Contributed to a large-scale LLM alignment and fine-tuning project focusing on Arabic. Tasks included evaluating AI-generated responses for relevance and accuracy, rewriting low-quality completions, and generating high-quality prompts and answers in both Modern Standard Arabic and Levantine dialect. Ensured adherence to quality guidelines, cultural appropriateness, and linguistic correctness. Provided structured feedback to support reinforcement learning from human feedback (RLHF). Worked with thousands of samples under tight deadlines while maintaining high QA scores.

2024 - 2024

Education

Work History