Research Engineer

# Research Engineer / Deep Learning Engineer (Computer Vision) – CDI## ShareID is hiringShareID 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 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 ExperienceJob Requirements Translation* **Minimum 4 years of experience** in deep learning applied to **computer vision**, with a portion of that experience in a **production environment** (startup, scale-up, industrial lab, etc.).* **Excellent command of:** + **Python**; + **PyTorch (or equivalent)**; + **Large-scale model training** (voluminous datasets, data augmentation, rigorous validation).* **Concrete experience in at least one of these areas:** + **Real-time vision** (tracking, video detection, high-performance pipeline); + **Biometrics** / face recognition / liveness; + **Document understanding** (document scanning, OCR, document augmentation, QA).* **Solid foundation in:** + **Statistics**, **optimization**, **supervised / self-supervised learning**; + Good reading comprehension of **literature** (ICCV, CVPR, NeurIPS, etc.).* **Experience working in a product environment:** + **Latency**, **robustness**, **hardware resource**, **security**, and **privacy constraints**.* Knowledge of **MLOps**: model deployment, monitoring, CI/CD, GPU/CPU serving.* Participation in **public benchmarks** or **publications** (arXiv, workshops, conferences).* **French**: professional proficiency (a plus); **English**: fluent (essential).Experience in **documentary fraud**, **KYC** (Know Your Customer), **cybersecurity**, or **digital identity**.* Contract Type: **Full-Time*** Start Date: **05 January 2026*** Location: **Paris*** Education Level: **Master's Degree*** Experience: **> 4 years*** **Occasional remote authorized** #J-18808-Ljbffr