Hello, I AM

Larbi SAIDCHIKH

<h1> I am a Machine Learning Engineer, AI Researcher, and Full-Stack Developer constantly seeking out innovative solutions to my everyday problems.<h1>

DATA MININGDATA SCIENCENATURAL LANGUAGE PROCESSINGMACHINE LEARNINGDEEP LEARNINGREINFORCEMENT LEARNINGCOMPUTER VISIONMOBILE DEVELOPMENTFRONT-END DEVBACK-END DEVUI/UX DESIGNGRAPHIC DESIGNDATA MININGDATA SCIENCENATURAL LANGUAGE PROCESSINGMACHINE LEARNINGDEEP LEARNINGREINFORCEMENT LEARNINGCOMPUTER VISIONMOBILE DEVELOPMENTFRONT-END DEVBACK-END DEVUI/UX DESIGNGRAPHIC DESIGN

About me

Hello! I am Larbi Saidchikh, a final-year student pursuing a Master’s Degree in Artificial Intelligence and Data Science at the National School of Artificial Intelligence. I am passionate about building intelligent systems and solving complex problems through Machine Learning and Full-Stack development. Currently, I am applying my skills as a Master Thesis Intern at EURECOM, focusing on Agentic AI. My background includes research internships at Siine and the Algerian Space Agency, where I worked on deep knowledge tracing and geospatial AI. I am actively seeking 2026 opportunities in Machine Learning Engineering, AI Research, and Full-Stack AI Products.

Skills & Languages

Programming Languages

PythonJavaScriptJavaC++CRPHPKotlinSQL

AI & Machine Learning

TensorFlowPyTorchScikit-learnDeep LearningNLPComputer Vision

Web Development

React.jsNext.jsNode.jsDjangoFlaskHTMLCSSTailwindBootstrap

Mobile Development

FlutterKotlin

Cloud & DevOps

GCPDockerKubernetes

Big Data

SparkHadoopHive

Tools & Others

GitNPMVite

Projects

RL for LLM Optimization

Developed a reinforcement learning–based framework to optimize the inference of the TinyLlama-1.1B model via pruning and mixed-precision quantization.

2025

Story4kids

Developed a mobile application for children to learn Arabic through interactive stories generated by fine-tuned LLM.

2025

WLAN Intrusion Detection with AI

This project enhances WLAN security through machine learning models capable of detecting wireless network attacks. The modeling pipeline includes both classification and anomaly detection models trained on realistic network traffic data.

2025