Hamza Ait Kabbour

Key Skills

Software

SuperAnnotate

Scale AI

Top Subject Matter

Large Language Models / Generative AI

Data science

Python

Top Data Types

Text

Computer Code Programming

Document

Top Task Types

RLHF

Classification

Segmentation

Fine-tuning

Evaluation/Rating

Data Collection

Computer Programming/Coding

Text Summarization

Text Generation

Object Detection

Function Calling

Prompt + Response Writing (SFT)

Freelancer Overview

Data Science/AI Trainer. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include SuperAnnotate and Scale AI. Education includes Master of Science, University Mohammed V, Faculty of Sciences (2024) and Bachelor of Science, University Mohammed V, Faculty of Sciences (2022). AI-training focus includes data types such as Text and labeling workflows including RLHF, Evaluation, and Rating.

Labeling Experience

Data Science/AI Trainer

SuperannotateTextRLHF

As a Data Science/AI Trainer at SME Careers via SuperAnnotate, I evaluated and fine-tuned large language models (LLMs) through targeted feedback and annotation. I used AI annotation tools to validate AI outputs and drive iterative model alignment. My work supported pipeline optimization and delivered measurable gains in model quality and performance. • Enhanced LLM training with precise annotations and RLHF techniques. • Provided actionable feedback to boost generative AI quality and reliability. • Utilized Python and annotation platforms to support AI evaluation. • Contributed to improving complex data workflows and LLM alignment.

As a Data Science/AI Trainer at SME Careers via SuperAnnotate, I evaluated and fine-tuned large language models (LLMs) through targeted feedback and annotation. I used AI annotation tools to validate AI outputs and drive iterative model alignment. My work supported pipeline optimization and delivered measurable gains in model quality and performance. • Enhanced LLM training with precise annotations and RLHF techniques. • Provided actionable feedback to boost generative AI quality and reliability. • Utilized Python and annotation platforms to support AI evaluation. • Contributed to improving complex data workflows and LLM alignment.

2025 - Present

Data Science (LLM QA/Evaluation)

Scale AIText

At Outlier (Scale AI), I performed validation and quality assurance of LLM outputs to ensure high business-standard alignment. I delivered focused feedback to support ongoing improvements in generative models. This contributed to quality increases in targeted areas of model deployment. • Audited and rated labeled outputs from large language models. • Applied annotation tools for model evaluation and calibration. • Documented and communicated issues to drive LLM enhancement. • Participated in large-scale generative AI projects with iterative annotation cycles.

At Outlier (Scale AI), I performed validation and quality assurance of LLM outputs to ensure high business-standard alignment. I delivered focused feedback to support ongoing improvements in generative models. This contributed to quality increases in targeted areas of model deployment. • Audited and rated labeled outputs from large language models. • Applied annotation tools for model evaluation and calibration. • Documented and communicated issues to drive LLM enhancement. • Participated in large-scale generative AI projects with iterative annotation cycles.

2024 - Present

Education

Work History