RESEARCH ENGINEER / DEEP LEARNING ENGINEER (COMPUTER VISION) – CDI

AboutShareID 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 DescriptionAs 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 WillDesign 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 ExperienceMust-have4 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-haveExpérience 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 ProcessSend UsYour CV or LinkedInLinks to GitHub / papers / demosA short note about a computer vision project you are proud of — and why.Contact: sawsen@shareid.ai (or your internal hiring email)Additional InformationContract Type: Full-TimeStart Date: 05 January 2026Location: Paris Education Level: Master's DegreeExperience: > 4 yearsOccasional remote authorized