Description

Je suis un data scientist et ingénieur MLOps expérimenté avec cinq années de pratique dans le domaine. Mon expertise se situe à l'intersection entre l'analyse de données avancée et l'ingénierie des opérations de machine learning, ce qui me permet de créer des modèles efficaces et de les déployer de manière optimale. Mon parcours professionnel m'a permis de développer des compétences solides en traitement de données, en conception de modèles prédictifs et en automatisation des pipelines, afin d'apporter des solutions performantes et évolutives aux problèmes complexes.

Languages

French
Native or bilingual
English
Fluent
Arabic
Native or bilingual

Workplace preferences

Can work on-site

Paris (up to 50km)

Swiss Life
AI/MLOps Engineer
December 2023 - Today (2 years and 6 months)
Paris, France
Design and deployment of scalable AI and MLOps solutions for knowledge management and enterprise search
applications.
• Selection and evaluation of LLMs and frameworks for Retrieval-Augmented Generation (RAG) and document
intelligence use cases.
• Development of data pipelines for document ingestion, chunking, post-processing, embedding, and vectorization.
• Implementation and benchmarking of retrieval techniques, including embedding-based, keyword-based, and hy-
brid search strategies.
• Performance evaluation of models based on quality, relevance, latency, and cost-effectiveness to optimize AI-
driven solutions.
Orange Business
AI/MLOps Engineer
September 2022 - April 2024 (1 year and 7 months)
Paris, France
AI for Telecom Infrastructure Investment Optimization :
• Analysis of network and geomarketing data for different sites in different countries to make optimal decisions for new deployment sites.
• Analysis of socio-economic and demographic data to optimize coverage and reduce churn rate.
• Building pipelines from data processing to model development and evaluation.
• Application of MLOps standards, including model management, experiment traceability, and process streamlining.
Cegid
Data Scientist
March 2019 - April 2022 (3 years and 1 month)
Paris, France
Automatic Generation of Financial Statements from Invoices:
• Automatic recognition of accounting documents performed by artificial intelligence combining Machine Learning and Deep Learning.
• Collaboration with the rest of the team to define the product roadmap.
• Evolution of existing Deep Learning and Machine Learning models (image processing, NLP...).
Ecole supérieure d'ingénieurs de recherche en matériaux et en InfoTronique (ESIREM)