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Amin F.AF

Amin F.

Senior ML Engineer | Computer Vision · MLOps · R&D

850 €/jour
Paris, FR
8-15 ans

Délai de réponse moyen : 1h

À propos de Amin

PhD en Machine Learning, plus de 10 ans d'expérience à l'intersection de la recherche ML et de l'ingénierie en production — couvrant la conception de systèmes ML end-to-end, l'architecture data, le cloud & HPC, et la computer vision.

J'interviens en tant qu'expert technique — conception et déploiement de pipelines ML, architecture data et infrastructure, computer vision — ou en tant que Research & ML Lead, structurant des équipes et des stratégies data dans des environnements scientifiques exigeants.

Je m'adapte au besoin : exécution technique, leadership, ou les deux.
  • Français

    Bilingue ou natif

  • Anglais

    Capacité professionnelle complète

En télétravail uniquement
Travaille majoritairement à distance

Expériences

  • Cairn Biosciences
    Founding Head of ML & Data Science
    BIOTECHNOLOGIES
    janvier 2019 - mai 2025 (6 ans et 4 mois)
    Halle Freyssinet - Station F, Paris, France
    AI-driven drug discovery startup.
    ○ Built and led the ML & data science function from the ground up — recruited and managed a team of 5 engineers and scientists, defined research and engineering strategy, secured competitive research funding including NIH grants and a PhD fellowship, and contributed to company-wide direction as a member of the Senior Scientific Committee.
    ○ Contributed to the company's scientific strategy and external visibility — building academic partnerships resulting in joint publications and co-supervised graduate students, conducting technology monitoring for the executive team, and listed as primary inventor on a pending international patent (PCT) covering core platform technology.
    ○ Engineered and deployed an end-to-end live-cell high-content screening platform processing terabytes of fluorescence microscopy video weekly — with analytical modules spanning cell segmentation, division detection and tracking, feature extraction, statistical analysis, and ML-driven downstream exploration — enabling systematic drug screening at a scale previously out of reach.
    ○ Architected the underlying data infrastructure from the ground up — including a proprietary cloud-native data format, parallelised HPC pipelines, and interactive dashboards for end-to-end experiment monitoring.
    ○ Drove ML and computational research across multiple projects — including NIH-funded work on laboratory automation at microfluidic scale and high-throughput drug screening — publishing findings in peer-reviewed journals on contrastive learning, cell segmentation, and representation learning.
    Tech Lead Computer Vision Research and Development (R&D) intelligence artificielle CTO
  • MINES Paris PSL
    Research Scientist (PhD)
    CENTRES DE RECHERCHE
    octobre 2014 - mai 2018 (3 ans et 7 mois)
    Paris, France
    PhD in Computer Vision and Pattern Recognition.
    ○ Designed novel algorithms for unsupervised and semi-supervised hierarchical image segmentation, video object segmentation, and semantic segmentation — results published in international conferences and journals.○ Implemented a graph-based hierarchical segmentation module in Smil (mathematical morphology Python library), adopted by the research group.
    ○ Organised a machine learning reading group for PhD students and taught industry-facing courses on deep learning at Mines Paris PSL.
    Computer Vision Research Research and Development (R&D) Data science Mathematics
  • Amadeus
    Software Engineer
    EDITION DE LOGICIELS
    février 2014 - octobre 2014 (8 mois)
    Sophia Antipolis, France
    Contributed to the pricing module of a large-scale airline ticket search engine and scripted data handling pipelines for high-volume transactional data.
    Programming Research and Development (R&D) Data Pipeline

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Formations

  • PhD
    Mines Paris PSL
    2018
    PhD
  • Generalist Engineering School (MSc)
    Ecole Centrale Méditerranée
    2013
    Generalist Engineering School (MSc)

Compétences

Catégories