Skills & Technologies
A showcase of the technologies and tools I work with
Python
SQL
Scala
C
MATLAB
PyTorch
Lightning
Hugging Face
TensorFlow
Scikit-learn
OpenCV
Gradio
PySpark
Ray
Apache Hadoop
CUDA
Python
SQL
Scala
C
MATLAB
PyTorch
Lightning
Hugging Face
TensorFlow
Scikit-learn
OpenCV
Gradio
PySpark
Ray
Apache Hadoop
CUDA
Python
SQL
Scala
C
MATLAB
PyTorch
Lightning
Hugging Face
TensorFlow
Scikit-learn
OpenCV
Gradio
PySpark
Ray
Apache Hadoop
CUDA
Work Experience
My professional journey and key achievements
Criteo
Machine Learning Engineer II
Oct. 2025 - Current
- ▹Reco Models team
- ▹Designed and managed end-to-end ML pipelines for recommendation sources (retargeting and contextual), including data preparation with lineage tracking, model training, and automated deployment
- ▹Implemented state-of-the-art models with novel feature engineering and user modeling approaches for improved retrieval performance
- ▹Configured A/B tests at scale (up to worldwide traffic), conducted statistical analysis, and managed production server pools for high-traffic environments
- ▹Acted as on-call engineer to troubleshoot critical issues in offline and online production systems
- ▹Mentored engineers and created comprehensive documentation to foster team knowledge sharing
Machine Learning Engineer
Oct. 2024 ‑ Sep. 2025
Machine Learning Research Intern (AI Lab)
Apr. 2024 ‑ Sep. 2024
- ▹Reco Research team, supervised by David Rohde
- ▹Subject: Optimizing Onsite Display Advertising through Deep Learning
Atos
AI & Computer Vision Research Intern (BDS - CV Lab)
Feb. 2023 - Aug. 2023
- ▹European project PREVENT PCP
- ▹Detection of abandoned luggage in video streams to improve station safety and limit false alerts
- ▹Implementation of score-based object/owner association algorithms, object tracking and re-identification
MBDA
Embedded AI Intern (Open Lab)
Apr. 2022 - Sep. 2022
- ▹Implementation of communication protocols, creation of an embedded Linux image on a Xilinx Zynq card, setting up a Vitis AI Docker environment, model benchmarking
Education
Academic background and degrees
Ecole Normale Supérieure Paris‑Saclay
MSc in Mathematics, Vision, Apprentissage (MVA)
- ▹World's leading #1 university in Mathematics (ARWU)
- ▹Courses: Deep Learning (theory and practice), Computer Vision, Object Recognition, Reinforcement Learning, Time Series Analysis, Natural Language Processing, Speech Processing, Convex Optimization, Probabilistic Graphical Models, Deep Generative Models, Signal Processing
- ▹Representative of a class of 250+ students
INSA Centre Val de Loire
MEng in Industrial Systems
- ▹Courses: Statistical Theory and Methods, Machine Learning, Computer Vision, Complex Systems Engineering, Risk Management
- ▹Student representative, active participation in various events (student council campaign, open days, etc.)
University of Tours
MSc in Applied Physics (Double Degree)
- ▹Courses: Automatics, Robotics, Cyber‑Physical Systems, Multiphysics Modelling
Tallinn University of Technology
School of Information Technologies (Erasmus)
- ▹Courses: Data Mining, Machine Learning, System Programming, Embedded Systems
Projects
Some academic and research projects
ENS Paris‑Saclay
Challenge Data Qube Research & Technologies (Collège de France)
Implementation of a football match results prediction model
Contrastive Learning for Molecular Retrieval
Implementation of a contrastive learning technique to enable the retrieval of molecules from natural language queries
Automating Video Segmentation
Automating video segmentation with "Segment Anything Meets Point Tracking"
Deep Temporal Clustering
Partial reimplementation of the paper "Deep Temporal Clustering: Fully Unsupervised Learning of Time‑Domain Features", analysis and testing
INSA Centre Val de Loire
PRISME Laboratory
Detection and tracking of micro‑scale magnetic robots on an ultrasound dataset (medical applications)
TalTech Embedded AI Research Lab
ML for Embedded Systems Course
Implementation of a garage door cycle detection model from an accelerometric data set on an STM32 board with X‑CUBE‑AI. Award: first prize 250€
About Me
Get to know more about my journey and what I bring to the table
My Story
I'm a passionate Machine Learning Engineer with expertise in recommendation systems, computer vision, and deep learning. I create innovative solutions that solve real-world problems in advertising and AI, currently working at Criteo as a Machine Learning Engineer II.
My journey in tech started with a curiosity about how things work, which quickly evolved into a deep passion for building software that makes a difference. I believe in continuous learning and staying up-to-date with the latest technologies and best practices in machine learning and AI.
I enjoy playing sports, traveling abroad to discover new cultures, and playing video games.
Machine Learning Expertise
Expertise in recommendation systems, computer vision, and deep learning
Production ML Systems
Experience in designing and managing end-to-end ML pipelines for high-traffic production environments
Research & Innovation
Academic background from ENS Paris-Saclay (MVA) with focus on novel ML approaches and state-of-the-art models
Big Data & Scalability
Proficient in Apache Spark, PySpark, Ray, and distributed computing for large-scale machine learning applications