def trouver_chemin():
    pourquoi = "sens"

    if pourquoi:
        comment = "chemin vers la lumière"
        return comment
    else:
        return "perdu"

print(trouver_chemin())
"

J'ai d'abord interrogé le Pourquoi avant de tracer le Comment, car nul chemin ne mène à la lumière s'il n'est guidé par le sens."

— Mariam Benali

Mariam Benali

Miriam Normal Version
Cyborg Metamorphosis Version
AI DEVELOPER | FULLSTACK DEVELOPER | MLOPS | COMPUTER VISION ENTHUSIASTAI DEVELOPER | FULLSTACK DEVELOPER | MLOPS | COMPUTER VISION ENTHUSIASTAI DEVELOPER | FULLSTACK DEVELOPER | MLOPS | COMPUTER VISION ENTHUSIASTAI DEVELOPER | FULLSTACK DEVELOPER | MLOPS | COMPUTER VISION ENTHUSIASTAI DEVELOPER | FULLSTACK DEVELOPER | MLOPS | COMPUTER VISION ENTHUSIASTAI DEVELOPER | FULLSTACK DEVELOPER | MLOPS | COMPUTER VISION ENTHUSIASTAI DEVELOPER | FULLSTACK DEVELOPER | MLOPS | COMPUTER VISION ENTHUSIASTAI DEVELOPER | FULLSTACK DEVELOPER | MLOPS | COMPUTER VISION ENTHUSIAST

About Me & My Vision

AI Engineer & Fullstack Developer | Building Intelligent & Scalable Solutions

Currently AI Engineer & Fullstack Developer, I design and develop intelligent solutions that combine artificial intelligence with modern web applications. My goal is to transform complex ideas into high-performing, practical, and scalable products.

My Projects

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Facial Detection Emotion
🧠
HR · NER · API · ML

Facial Detection Emotion

Ce projet utilise Deep Learning pour détecter les visages dans des images et prédire les émotions associées. Il combine OpenCV, TensorFlow/Keras, et FastAPI pour créer une API capable de traiter des images en temps réel.

PythonTensorFlowOpenCVFastAPICNN
HR-Pulse
🧠
HR · NER · API · ML

HR-Pulse

Automated Job Offer Analysis Platform

A full-stack AI-powered platform that automates the analysis of job offers, extracts key skills using NER, predicts salary ranges, and exposes everything through a modern API — fully containerized and observable.

PythonFastAPINERHugging FaceDockerPostgreSQLMLflow
RetentionAI
🧠
HR · NER · API · ML

RetentionAI

Smart HR Assistant for Predicting Employee Turnover

RetentionAI is a full-stack HR analytics platform combining supervised machine learning and generative AI. It exposes a secure JWT-based API, uses PostgreSQL for data persistence, and is containerized with Docker to deliver an explainable, scalable, and production-ready solutio

PythonDockerJWTMatplotlibSupervised Machine LearningFastAPIScikit-learnPrompt EngineeringGenerative AI
Quant-AI_pr-diction_prix_Bitcoin
🧠
HR · NER · API · ML

Quant-AI_pr-diction_prix_Bitcoin

End-to-End ML Deployment Platform

The project aims to create an end-to-end platform that collects Binance data, calculates technical indicators, trains a Machine Learning model to predict the price of Bitcoin over the next 10 minutes, and exposes the results via a REST API

DockerData ScienceMachine LearningAirflowJWTPySparkData EngineeringRegression ModelsMLflowFastAPI
RAG-AI_Assistant
🧠
HR · NER · API · ML

RAG-AI_Assistant

AI Assistant using RAG for support IT

An internal intelligent assistant capable of reliably answering IT technicians’ questions based on an IT support PDF (procedures, incidents, FAQs)

postgresmachine-learningjwtjupyterdocker-composepostgresqlci-cdpython3ragmlflowfastapihuggingfacelangchain
NLP-Classification_Support_Tickets
🧠
HR · NER · API · ML

NLP-Classification_Support_Tickets

NLP-based classification of support tickets

End-to-end NLP batch pipeline for IT support ticket classification, covering data exploration, text preprocessing

pythonnlpkubernetesmachine-learninggrafanaprometheusmlopsgithub-actionshuggingfaceevidentlychromadb
LSM-TALK
🧠
HR · NER · API · ML

LSM-TALK

AI-based sign language recognition system

This repository showcases an AI-based sign language recognition system using MediaPipe for real-time keypoint extraction and LSTM neural networks for temporal gesture recognition, aiming to improve accessibility through intelligent human–computer interaction.

PythonMediaPipeLSTMComputer VisionAI

My Skills

🐍 Programming

Solid foundations in scripted, queried, and dynamic programming across data, backend, and web contexts.

PythonSQLJavaScript

🧠 AI / Machine Learning

Building and deploying intelligent models — from image recognition to language understanding and retrieval-augmented generation.

Computer VisionTensorFlowKerasLSTMCNNNLPLLMHugging FaceRAGScikit-learn

⚙️ Backend & APIs

Designing fast, secure, and scalable server-side logic and authenticated API pipelines.

FastAPIDjangoREST APIsJWT

🗄️ Data & Databases

Structuring, querying, and transforming data for reliable analytical and production pipelines.

PostgreSQLAzure SQLPandasNumPyData Processing

☁️ Cloud & MLOps

End-to-end ML lifecycle management — from containerized deployments to observability and automated pipelines.

DockerPodmanTerraformGitHub ActionsCI/CDAzureKubernetesMLflowEvidentlyOpenTelemetryJaeger

🖥️ Frontend

Crafting modern, responsive, and data-driven interfaces for web and ML applications.

Next.jsTailwindCSSStreamlitHTMLCSS

My Experience

The positions I have worked in my career so far

job-1.py
terminal
git
12345678
job = {
"title": "AI Engineer",
"from": "Oct 2025",
"to": "Mars 2026",
"company": "Simplon",
"type": "Certificate",
}
job-2.py
terminal
git
12345678
job = {
"title": "Manager",
"from": "Dec 2019",
"to": "Nov 2024",
"company": "Business Family",
"type": "Personal",
}
job-3.py
terminal
git
12345678
job = {
"title": "Telesales & Customer Service Agent",
"from": "June 2015",
"to": "Sept 2019",
"company": "Webhelp",
"type": "CDI",
}
job-4.py
terminal
git
12345678
job = {
"title": "Webmarketer",
"from": "Jan 2013 ",
"to": "Apr 2015",
"company": "COMELIA",
"type": "CDI",
}
job-5.py
terminal
git
12345678
job = {
"title": "Banking Customer Service",
"from": "Jul 2012",
"to": "Dec 2012",
"company": "Banque Populaire",
"type": "CDD",
}
job-1.py
terminal
git
12345678
job = {
"title": "Training",
"from": "Jul 2011",
"to": "Aug 2011 ",
"company": "Agence National Des Port",
"type": "Training",
}

Let's Work Together

Have a project in mind? Let's build something exceptional together.