Open to Work

6-month internship • Available early March 2026

Building LLM-powered systems that are practical, reliable, and measurable.

Final-year Master’s (M2) student in NLP at Université de Lorraine (IDMC). Focus: LLM fine-tuning, RAG pipelines, Annotation Workflows, and model interpretability—from data → modeling → evaluation → deployment.

Get in touch View projects

LinkedIn GitHub Link

Core Skills

NLP • Applied AI

LLMs

Fine-tuning & RAG

HITL

Annotation Loops

XAI

Interpretability

Deploy

End-to-end delivery

Looking for: End-of-studies internship (Stage de fin d’études) in Applied Science / NLP Engineering.
Start: early March 2026 • Duration: 6 months

Watch Featured Project Demos

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Featured Projects

Projects in LLMs, RAG, interpretability, and research analytics.

Watch App Demo

AnnotaLoop — LLM-Driven Document Annotation

Desktop App

A cross-platform desktop app that reduces annotation time by upto 83%. Combines LLM suggestions with human-in-the-loop validation to produce structured labeled data at scale.

Cross-Platform Desktop GUI HITL LLMs

Project Website Source Code

Video Demo

Researchlytic — Research Trends & Discovery Platform

Product

A bibliometric analytics platform built on OpenAlex (250M+ works, 90M+ authors) to explore research trends across institutions, countries, and time.

Bibliometrics OpenAlex Dashboards NLP

Live Demo Source Code

Video Demo

Intrinsic Evaluation of French Word Embeddings

M2 Supervised Project

A research study analyzing gender encoding across 33K+ French words using FlauBERT. Utilized SHAP & LIME to demonstrate distributed encoding patterns, achieving 99% accuracy on adjective tasks.

Interpretability FlauBERT SHAP/LIME Representation Analysis

Live Demo Source Code

Video Demo

Hybrid Intelligent Systems (HISs) Ontology

Coursework

An interactive taxonomy of Hybrid Intelligent Systems covering AI paradigms, evaluation metrics, and real-world applications.

Ontology Knowledge Graph Interactive Web

Live Demo Source Code

About

I build and ship NLP systems end-to-end: data → modeling → evaluation → deployment.

Profile

Final-year Master’s (M2) student in NLP at Université de Lorraine with experience in LLM fine-tuning, RAG pipelines, and model interpretability.

Seeking a 6-month end-of-studies internship starting early March 2026.

What I bring

Practical GenAI: fine-tuning, prompts, evaluation, and deployment trade-offs.
RAG engineering: retrieval, chunking, embeddings, FAISS/Pinecone, quality checks.
Interpretability: SHAP/LIME + attribution analysis for debugging & trust.
Product mindset: clean demos, strong UX, and measurable outcomes.

Technical Skills

Tools and frameworks used across my NLP and GenAI projects.

GenAI & LLMs

LLM Fine-tuning RAG Pipelines LangChain Prompt Engineering BERT LLaMA

Deep Learning & NLP

PyTorch Hugging Face scikit-learn spaCy Pandas

Engineering

Python SQL PHP JavaScript Bash Docker Git/GitHub Linux AWS (S3)

Vector Databases

FAISS Pinecone

Languages

English (Fluent) Urdu/Punjabi (Native) French (Basic)

Experience & Education

Roles, responsibilities, and academic background.

Experience

Creator & Full Stack Engineer

Jun 2022 — Sept 2024

Researchlytic (Remote)

Engineered a large-scale bibliometric analysis engine using OpenAlex to index metadata and visualize research trends.
Built interactive dashboards in PHP/MySQL with filtering by region, time, institutions, and venues.
Designed scoring signals combining volume, citation impact, and open-access indicators.