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Achehboune Y.AY

Achehboune Y.

Computer Vision Engineer | Deep Learning

€140/day
Clermont-Ferrand, FR
0-2 years

Average response time: 1 hour

About Achehboune

As Computer Vision R&D Engineer at Endoscopy and Computer Vision Lab, where I contributed to projects focused on medical image analysis and AI solutions. This experience allowed me to work with real-world medical data and develop practical pipelines used in research and experimentation.

My strengths include building end-to-end pipelines for medical image preprocessing, segmentation, and classification. I work with volumetric data (3D scans), ROI extraction, and mask alignment, ensuring clean workflows. I regularly implement and adapt state-of-the-art methods from research papers, and I am experienced in reproducing experiments and evaluating models.

I hold a Master’s degree in Advanced Machine Learning and multimedia intelligence and focus on delivering reliable, well-structured solutions for AI applications.
  • Arabic

    Native or bilingual

  • English

    Fluent

  • French

    Fluent

Remote only
Primarily works remotely

Experience

  • EnCoV
    R&D Engineer
    MEDICAL
    February 2025 - Today (1 year and 4 months)
    Clermont-Ferrand, France
    • Designed and implemented convolutional neural networks (CNNs) for extracting robust radiomic features from medical imaging data (CT scans).
    • Built end-to-end data pipelines including preprocessing, normalization, and data augmentation to improve model generalization.
    • Engineered and analyzed radiomic features to support predictive modeling tasks in medical imaging.
    • Evaluated model performance using advanced metrics (R², MAE, validation curves), leading to iterative improvements in robustness and reliability.
    • Contributed to experimentation workflows, including dataset exploration (EDA) and model benchmarking.
    Machine Learning & Deep Learning Transfer Learning model evaluation Feature Engineering Research and Development (R&D)
  • 3D SMART FACTORY
    R&D Engineer
    February 2024 - January 2025 (11 months)
    Project: Adaptive Cognitive Assessment System for Recruitment

    Designed and implemented an NLP pipeline to extract and structure key information from candidate CVs.
    Built an adaptive assessment system that generates and evaluates personalized interview questions using LLMs (via Gemini API) and prompt engineering techniques.
    Developed an interactive web interface using Streamlit to deliver assessments and visualize results.
    Integrated CV analysis with dynamic question generation to support smarter, automated recruitment workflows.
    Machine Learning & Deep Learning Python Natural Language Processing (NLP) Data scientist NLP Large Language Models (LLMs)

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Education

  • Master's in Advanced Machine Learning and
    Faculty of Sciences Dhar El Mahraz
    2026
    Master's in Advanced Machine Learning and
  • Bachelor's in Science and Techniques
    Faculty of Sciences and Techniques of Errachidia
    2024
    Bachelor's in Science and Techniques

Skill set

Categories