Nour M.

Key Skills

Software

Data Annotation Tech

Other

Top Subject Matter

LLM training data annotation and evaluation

Legal Services & Contract Review

Regulatory Compliance & Risk Analysis

Top Data Types

Text

Image

Audio

Document

Top Task Types

Polygon

Segmentation

Object Detection

Text Generation

Question Answering

Evaluation/Rating

Freelancer Overview

AI Training Contributor - Data Annotation & Evaluation. Brings 5+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Data Annotation Tech. Education includes Bachelor of Science, Cairo University. AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Fine Tuning.

Labeling Experience

AI Evaluation Contributor - Outlier AI

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Contributed to AI model evaluation and data preparation workflows across Outlier AI platforms, focusing on prompt evaluation and response ranking. Applied critical thinking to judge outputs against quality rubrics and inform downstream improvements. Worked in a structured human-in-the-loop setup to guide, correct, and validate automated AI agent outputs. • Performed prompt and response evaluation against predefined rubrics • Ranked and validated AI outputs to support quality fine-tuning • Collaborated within human-in-the-loop processes • Ensured consistency and quality of model outputs

2024 - Present

AI Training Contributor - Data Annotation & Evaluation

Data Annotation TechText

Contributed to AI model training pipelines through data annotation and response ranking to improve LLM quality. Evaluated AI outputs against quality rubrics and used results to inform fine-tuning and reinforcement learning workflows. Participated in a structured human-in-the-loop process to guide, correct, and validate automated agent responses.•Performs prompt evaluation and response ranking for model training data.•Assesses outputs using quality rubrics to support fine-tuning/reward modeling.•Provides human expert judgment to validate or correct generated responses.•Operates within an in-the-loop QA framework for continuous improvement.

2024 - Present

AI Quality Evaluator (Human-in-the-Loop) - Outlier AI

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Contributed to AI model training pipelines through data annotation, prompt evaluation, and response ranking to improve LLM quality. Applied quality rubrics to assess AI outputs and inform downstream fine-tuning and reinforcement workflows. Operated in a human-in-the-loop environment to validate and correct automated agent responses. • Data annotation and prompt evaluation • Response ranking against quality rubrics • Support for fine-tuning and reinforcement workflows • Human-in-the-loop validation and feedback

2024 - Present

AI Training Contributor - Data Annotation & Evaluation (Outlier AI, Welocalize, DataAnnotation.tech)

OtherText

Contributed to AI model training pipelines by performing data annotation, prompt evaluation, and response ranking to improve LLM output quality. Assessed AI outputs against quality rubrics and used the results to inform downstream model fine-tuning and reinforcement learning workflows. Worked in structured human-in-the-loop processes to validate, correct, and guide automated AI agent responses.• Annotated data for LLM training and quality improvement.• Evaluated prompts and model responses using defined rubrics.• Ranked responses to support training signal generation.• Performed expert review to ensure consistency and reliability of outputs.

2024 - Present

AI Training Contributor - Data Annotation & Evaluation (Part-time) at Outlier AI / Welocalize / DataAnnotation.tech

Data Annotation TechText

Contributed to AI model training pipelines performing data annotation, prompt evaluation, and response ranking to improve LLM quality. Assessed AI outputs against quality rubrics within structured human-in-the-loop workflows. Provided expert judgment to guide, correct, and validate automated AI agent outputs. • Performed prompt evaluation and response ranking • Annotated and quality-checked model outputs using rubrics • Supported fine-tuning and reinforcement learning workflows via feedback • Worked across Outlier AI, Welocalize, and DataAnnotation.tech pipeline processes

2024 - Present

Education

Work History