Marouani Mohamed Habib

Key Skills

Software

Appen

Top Subject Matter

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Top Data Types

Text

Top Task Types

Classification

Text Generation

Transcription

Freelancer Overview

I am a detail-oriented full stack developer with a strong foundation in data analysis and hands-on experience building scalable web and mobile applications. My background includes developing complex platforms for domains such as food delivery and telemedicine, where I implemented real-time data tracking, user authentication, and analytics dashboards. I am proficient in structuring and managing databases with PostgreSQL, MySQL, and MongoDB, and have integrated RESTful and GraphQL APIs to ensure data accuracy and consistency. My experience with Agile teams and cloud deployment, along with my understanding of AI/ML integration basics, allows me to approach data labeling and annotation tasks with a focus on quality, efficiency, and compliance. I am passionate about contributing to high-quality AI training data pipelines, especially in projects involving user interactions, medical data, and real-time systems.

Labeling Experience

AI Text Annotation & Model Evaluation Project

AppenTextClassificationText Generation

Worked on AI training projects focused on improving large language models through high-quality text annotation and response evaluation. Tasks included labeling user prompts by intent and sentiment, evaluating AI-generated responses for correctness, relevance, and safety, and identifying hallucinations or logical inconsistencies. The project involved processing large datasets while strictly following detailed annotation guidelines and quality benchmarks. Regular quality checks were conducted to ensure consistency and accuracy across all labeled data

Worked on AI training projects focused on improving large language models through high-quality text annotation and response evaluation. Tasks included labeling user prompts by intent and sentiment, evaluating AI-generated responses for correctness, relevance, and safety, and identifying hallucinations or logical inconsistencies. The project involved processing large datasets while strictly following detailed annotation guidelines and quality benchmarks. Regular quality checks were conducted to ensure consistency and accuracy across all labeled data

2024 - 2025

Education

Work History