Description

I am a Machine Learning engineer and PhD candidate specialized in computer vision and deep learning. I help clients solve concrete problems quickly, from debugging Python code to building and improving machine learning models.

🔧 What I can do for you:

Debug and optimize Python code (NumPy, PyTorch, etc.)

Help with Machine Learning / Deep Learning projects

Implement computer vision solutions (image processing, detection, matching)

Support students or teams on technical projects (fast and clear explanations)

⚡ I focus on:

Fast delivery

Clear communication

Practical and efficient solutions

🎓 Background:

Engineering degree from ENSEIRB-MATMECA + Master’s degree in Signal and Image Processing, currently pursuing a PhD in Machine Learning & Computer Vision.

I am available for short missions, urgent tasks, or ongoing support.

Languages

English
Native or bilingual
French
Native or bilingual
German
Basic
Arabic
Native or bilingual

Workplace preferences

Remote only

Primarily works remotely

CNRS
Ingénieur chercheur : Deep Learning & Computer vision
TECH
March 2026 - Today (4 months)
Orléans, France
⋄ Développement de méthodes d’analyse d’images cosmétiques basées sur
l’intelligence artificielle pour automatiser l’évaluation des caractéristiques
de jeunesse du visage.
⋄ Conception et adaptation de modèles de deep learning (segmentation et
classification) à partir d’architectures CNN afin d’améliorer la précision et la
robustesse des analyses.
⋄ Exploitation des résultats d’analyse pour mesurer l’efficacité des soins
cosmétiques et étudier les corrélations entre indicateurs de jeunesse et
types de traitements.
Deep Learning CNN Machine learning Computer Vision Stable Diffusion
Institut Denis Poisson
PhD Researcher: Deep Learning & Mathematics
TECH
December 2025 - Today (7 months)
Orléans, France
⋄ Development of artificial intelligence–based cosmetic image analysis
methods to automate the evaluation of facial youth-related characteristics.
⋄ Design and adaptation of deep learning models (segmentation and classi
fication) based on CNN architectures to improve the accuracy and robustness
of the analyses. ⋄ Exploitation of analysis results to assess the effectiveness of cosmetic
treatments and to study correlations between youth indicators and treatment
types.
Deep Learning CNN Image classification Transformers Computer Vision
Orange Innovation
Deep Learning & Computer Vision Engineer
TELECOMMUNICATIONS
March 2025 - August 2025 (5 months)
Belfort, France
⋄ Improvement of a deep learning model for the automatic extraction of
walls, doors, and windows from architectural floor plan images. ⋄ Optimization of model architecture, hyperparameters, and data augmenta
tion techniques to enhance accuracy. ⋄ Development of post-processing methods to refine vectorization, including
point realignment and segment merging.
Deep Learning Data science Python TensorFlow Pytorch