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Zakaria BasraouiZB

Zakaria Basraoui

ML/AI Enigneer | Computer Vision | Automation

570 €/jour
Antwerpen, BE
0-2 ans

Délai de réponse moyen : 1h

À propos de Zakaria

Computer Vision Engineer based in Belgium, with 1.5 years of production experience in ML/CV systems.

What I offer:
- Defect detection & quality control automation
- Object detection and classification models
- Edge deployment (Jetson Nano, Coral, Raspberry Pi)
- Dataset creation, labeling & model training
- Real-time inference pipelines

Tech stack: Python, PyTorch, TensorFlow, OpenCV, YOLO, scikit-learn.

I primarily work with manufacturing companies looking to automate manual inspection.
  • Anglais

    Capacité professionnelle complète

  • Français

    Capacité professionnelle limitée

  • Néerlandais

    Bilingue ou natif

  • Arabe

    Bilingue ou natif

Accepte de travailler sur site
Antwerpen (jusqu’à 50 km)

Expériences

  • Innops
    FOUNDER
    AGENCE & SSII
    septembre 2025 - Aujourd'hui (9 mois)
    Brussels, BU, Belgium
    • AI-focused consultancy for industrial inspection and robotics use cases.
    • Developing internal prototypes and reusable building blocks (Python, computer vision workflows).
    • Available for ad-hoc consulting (AI/software support and integrations when relevant).
    Computer Vision Machine learning software-architecture
  • Havencentrum
    FREELANCE EDUCOACH
    EDUCATION & E-LEARNING
    août 2024 - septembre 2025 (1 an et 1 mois)
    Antwerpen, Belgique
    Facilitated interactive workshops and excursions for youth (ages 10–18), managed
    group dynamics and scheduling, and coordinated sessions using provided
    materials and digital administration tools.
  • Movu Robotics,
    AI DEVELOPER
    juillet 2024 - Aujourd'hui (1 an et 11 mois)
    Lokeren, OV, Belgium
    • •Developed computer-vision solutions for industrial quality control in a warehouse environment.
    • •Built and maintained Python-based AI pipelines, focusing on reliability, modularity, and production readiness.
    • •Validated models in a live environment, achieving high-precision performance (>95%) through confidence-threshold tuning.
    • •Applied ML lifecycle and deployment practices to move prototypes toward deployable features.
    • •Collaborated cross-functionally to align technical decisions with operational constraints.
    • •Facilitated interactive workshops and excursions for youth (ages 10–18), managed group dynamics and scheduling, and coordinated sessions using provided materials and digital administration tools.

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Formations

  • Bachelor of Applied Science
    Erasmushogeschool
    2026
    Bachelor of Applied Science
  • Bachelor of Applied Science
    AP Hogeschool
    2023
    Bachelor of Applied Science

Catégories