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Fatima Ezzahra Bouzidi IdrissiFE

Fatima Ezzahra Bouzidi Idrissi

Tech Lead ML AI

€800/day
Boulogne-Billancourt, FR
8-15 years
Python
Google Cloud
Artificial Intelligence
Retrieval-Augmented Generation (RAG)
AI Agent

Average response time: 1 hour

Freelancer profile translated to English.
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About Fatima Ezzahra

Mathhematician, Lead Tech ML/AI. I am obsessed with optimization: finding the most elegant angle of attack for a complex problem.

9 years of technical leadership in demanding environments (banking, insurance, automotive, energy). I offer AI architecture, technical leadership, and technical vision direction. RAG, multi-agent systems, MLOps. No room for solutions that don't survive in production.

My conviction: architectural thinking always comes before technology. You must first understand the business problem, identify its mathematical structure, and then design something that holds up.

Certified GCP. Author on RAG architectures. What truly fascinates me: the space where conceptual elegance meets real-world complexity. Where math meets production.

I offer technical leadership, AI architecture, and strategic consulting. Missions where technical vision truly matters.

  • French

    Native or bilingual

  • English

    Fluent

  • Arabic

    Fluent

Can work on-site
Boulogne-Billancourt (up to 50km)

Experience

  • RENAULT DIGITAL
    Tech Lead Data & AI
    AUTOMOBILE
    July 2025 - March 2026 (8 months)
    Paris, France
    ▸ Technical Management: Simultaneous leadership of two multidisciplinary teams (developers, ML Engineers, Data Scientists, DevOps, Architects): systematic code reviews, pair programming sessions, defining quality standards and coding conventions
    ▸ RAG Architecture: Design of the complete RAG pipeline architecture: document ingestion, chunking, embedding generation, vector indexing, and semantic search API
    ▸ Infra Optimization: Migration of orchestration from Airflow/Composer to Cloud Workflows, leading to significant infrastructure cost reduction and improved scalability
    ▸ Microservices: Development of containerized FastAPI microservices, deployed on Cloud Run, for large-scale document processing and transformation
    ▸ Vector Database: Implementation of MongoDB Atlas as a vector database for storing and searching document embeddings
    ▸ Team Practices: Writing exhaustive technical documentation, implementing Full Focus Time to maximize team productivity
    🔧Python, FastAPI, GCP (Cloud Run, Cloud Workflows, Cloud Functions), MongoDB Atlas, Terraform, GitLab, Docker
    Google Cloud Platform (GCP) MLOps Artificial Intelligence MLOps
  • SFEIR
    ML / AI CONSULTANT
    DIGITAL AND IT
    February 2022 - July 2025 (3 years and 5 months)
    Paris, France
    Alongside client missions, active involvement in SFEIR's internal activities through various cross-functional roles and key responsibilities.
    ▸ Recruitment: Technical evaluation of candidates during playoffs (recruitment technical tests) to identify and select new Data & ML profiles
    ▸ Expertise Circles: Active member of the Data Circle and ML/AI Circle: knowledge sharing, technological watch, structuring SFEIR's Data/AI offering
    ▸ Conferences & Talks: Internal and external presentations on Data, ML, and AI topics: conferences, workshops, expertise sharing with teams and clients
    ▸ Pre-sales: Participation in pre-sales and commercial pitches: technical scoping, effort estimation, presenting the offering to prospects
    ▸ CSE & Representative: Elected member of the CSE (Social and Economic Committee) and sexual harassment representative
    Artificial Intelligence Google Cloud Platform (GCP) MLOps Natural Language Processing (NLP) Retrieval-Augmented Generation (RAG)
  • SLB (Schlumberger)
    Cloud Data Engineer
    ENERGY AND UTILITIES
    May 2025 - July 2025 (2 months)
    Paris, France
    ▸ Architecture & Parsing: Design and development of an intelligent dispatcher system via Azure Functions: automatic file type detection, routing to the appropriate parser (Helios, Coriolis, eFire…), specialized parsing of industrial files and export in Parquet format
    ▸ GCP Migration to Azure: Migration of existing pipelines from Google Cloud Platform to Azure: service adaptation, storage and trigger reconfiguration
    ▸ Infrastructure & Resilience: Implementation of a complete Azure infrastructure (Functions, Storage, Application Insights) with a modular error management architecture and deployment automation
    🔧Python, Azure Functions, Azure Blob Storage, Application Insights, Parquet, Makefile, CI/CD
    Google Cloud Platform (GCP) AI Agent MLOps Python Artificial Intelligence
Check out Fatima Ezzahra's experience

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Education

  • ML Engineer & Data Engineer
    ML Engineer & Data Engineer
  • Professional Machine Learning Engineer
    Google Cloud Platform
    Professional Machine Learning Engineer
Check out Fatima Ezzahra's education

Skill set

Infra as Code
Scripting Automation

Categories