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Dhia M.DM

Dhia M.

ML Engineer | Data Scientist | GenAI, LLM

€400/day
Paris, FR
3-7 years

Average response time: 1 hour

Freelancer profile translated to English.
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About Dhia

Machine Learning & Generative AI Engineer | LLM | Computer Vision


ML Engineer from Paris-Saclay, I design robust and scalable Artificial Intelligence solutions. Bilingual (English C2 / French C1), I support companies from raw data to the deployment of high-performing models.

What I can do for you:

  • Machine Learning & Predictive Modeling:Development and optimization of supervised and unsupervised algorithms for data prediction and segmentation. Experience in feature extraction, complex data processing, and performance evaluation.
  • Generative AI & LLM:Development of RAG (Retrieval-Augmented Generation) systems to query your company data without hallucinations. Expertise in LangChain, Hugging Face, and Knowledge Graph integration.
  • Computer Vision:Design of image detection and segmentation models (CNN, Mask R-CNN). Hands-on experience at GamhScan (AgriTech) on industrial quality analysis.
  • Data Engineering & MLOps:Creation of ETL pipelines and cleaning of complex and experimental datasets to ensure algorithm reliability.

Available for development, prototyping (PoC), or technical consulting missions. Let's discuss your project!
  • English

    Native or bilingual

  • French

    Native or bilingual

  • Arabic

    Native or bilingual

Can work on-site
Paris (up to 50km), Lyon (up to 10km)

Experience

  • IFP Energies nouvelles
    R&D AI Engineer
    AUTOMOBILE
    February 2026 - Today (4 months)
    Rueil-Malmaison, France
    The objective of this project was to develop a hybrid approach (Physics-Informed Machine Learning)
    Machine Learning Data Science Big Data Data Engineer Python
  • IBISC
    R&D Engineer (Academic Project)
    January 2025 - May 2025 (4 months)
    Évry, France
    Subject:Design of a neuro-symbolic architecture (LLM + Knowledge Graph) for personalized learning.

    • Innovation:The system does not just retrieve information (classic RAG), it uses the Knowledge Graph to model the student's skill level.

    • Result:The LLM dynamically adjusts the complexity of its response (vocabulary, technical depth) based on the "Level" node detected in the graph, reducing the cognitive load for the learner.

    Stack: Python, LangChain, Neo4j (Graph DB), OpenAI API, Advanced Prompt Engineering.
    LLM Langchain Neo4j Prompt Engineering Python
  • GamhScan - Startup Agricole
    Junior Data Scientist
    AGRICULTURE
    February 2023 - September 2023 (7 months)
    Batna, Algeria
    • Contribution to the preparation and cleaning of a large dataset of wheat seed images to train a deep learning model.
    • Participation in the optimization of a system based on a hybrid approach (Mask R-CNN, CNN with transfer learning, classic computer vision).
    Deep Learning Machine Learning Scikit-learn MLOps Computer Vision

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Education

  • Master Computer & Network Systems - Autonomous Systems
    Université Paris-Saclay
  • Master - Intelligent Computer Systems Engineering
    University of Algiers 1
    2024

Certifications

Skill set

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