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Research Engineer / Deep Learning Engineer (Computer Vision) – CDI

ShareID is hiring!

About

ShareID delivers real-time, secure authentication using official ID documents and a simple smile. Our AI-powered solution verifies IDs from over 120 countries with 99.9% accuracy, confirms document ownership, and ensures user liveness—without storing personal data. With our patented technology, users get a reusable digital identity and ongoing access to verifiable credentials.

Our mission is to transform authentication by making it seamless, trustworthy, and user-friendly.

Founded at Station F by Sara, a financial engineer with 9+ years in regulatory risk, and Sawsen, a PhD in computer vision with experience at Cisco’s Innovation Lab, ShareID combines deep expertise in security, AI, and digital identity.

Job Description

As a senior member of the R&D team, you will design, train, optimize, and deploy deep learning models for ShareID’s core products:

Document Verification, Face Authentication, Liveness, and Fraud Detection.

You will work on computer vision problems involving images, videos, and temporal sequences in highly adversarial (fraud-prone) environments.

You will:

  • Design and implement advanced computer vision models, with a focus on:

    • identity document analysis,
    • forgery / tampering detection,
    • face authentication and liveness,
    • deepfake / spoofing attack detection,
    • video-based temporal modeling and tracking.

  • Experiment with state-of-the-art architectures:

    • transformer-based models (ViT, DETR-like, SAM, etc.)
    • diffusion / generative models for augmentation or anomaly detection,
    • latency-optimized networks (quantization, pruning, distillation).

  • Own end-to-end research cycles:

    • literature review,
    • prototyping and experimentation,
    • evaluation on large-scale datasets,
    • productization with engineering teams.

  • Collaborate cross-functionally with Product, Risk, Fraud, and Engineering to bring research ideas into production.

  • Contribute to ShareID’s scientific culture:

    • present papers, lead knowledge-sharing sessions,
    • guide junior ML engineers and interns,
    • optionally participate in benchmarks or publications.

Preferred Experience

Must-have

  • 4 ans d’expérience minimum en deep learning appliqué à la vision par ordinateur, dont une partie en environnement produit (startup, scale-up, labo industriel, etc.).

  • Excellente maîtrise de :

    • Python ;
    • PyTorch (ou équivalent) ;
    • l’entraînement de modèles à grande échelle (datasets volumineux, data augmentation, validation rigoureuse).

  • Expérience concrète sur au moins un de ces sujets :

    • vision temps réel (tracking, détection vidéo, pipeline performant) ;
    • biométrie / face recognition / liveness ;
    • document understanding (scan de documents, OCR, augmentation de documents, QA).

  • Solides bases en :

    • statistiques, optimisation, apprentissage supervisé / auto-supervisé ;
    • bonne lecture de la littérature (ICCV, CVPR, NeurIPS, etc.).

  • Habitude de travailler dans un environnement produit :

    • contraintes de latence, robustesse, ressources hardware, sécurité, privacy.

Nice-to-have

  • Expérience en fraude documentaire, KYC, cybersécurité ou identité numérique.

  • Connaissances en MLOps : déploiement de modèles, monitoring, CI/CD, serving GPU/CPU.

  • Participation à des benchmarks publics ou publications (arXiv, workshops, conférences).

  • Français : niveau professionnel (un plus) ; anglais : courant (indispensable).

Recruitment Process

Send us:

  • Your CV or LinkedIn

  • Links to GitHub / papers / demos

  • A short note about a computer vision project you are proud of — and why.

Contact: sawsen@shareid.ai (or your internal hiring email)

Additional Information

  • Contract Type: Full-Time
  • Start Date: 05 January 2026
  • Location: Paris
  • Education Level: Master's Degree
  • Experience: > 4 years
  • Occasional remote authorized
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