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RESEARCH ENGINEER
il y a 3 semaines
RESEARCH ENGINEER / DEEP LEARNING ENGINEER (COMPUTER VISION) – CDI 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. About Founded in Station F, ShareID combines deep expertise in security, AI and digital identity. Our mission is to transform authentication by making it seamless, trustworthy and user‑friendly. The founding team includes a financial engineer with 9+ years in regulatory risk and a PhD in computer vision with experience at Cisco’s Innovation Lab. Job Description As a senior member of the R&D team, you will design, train, optimise 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 focused on identity document analysis, forgery/tampering detection, face authentication & liveness, deepfake/spoofing attack detection, and video‑based temporal modelling and tracking. Experiment with state‑of‑the‑art architectures, including transformer‑based models (ViT, DETR‑like, SAM, etc.), diffusion/generative models for augmentation or anomaly detection, and latency‑optimised networks (quantisation, pruning, distillation). Own end‑to‑end research cycles: literature review, prototyping, experimentation, evaluation on large‑scale datasets and productisation 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, and optionally participate in benchmarks or publications. Preferred Experience Minimum 4 years of deep‑learning experience applied to computer vision, including a production environment (startup, scale‑up, industrial lab, etc.). Excellent command of Python, PyTorch (or equivalent) and large‑scale model training (voluminous datasets, data augmentation, rigorous validation). Concrete experience in at least one of the following: real‑time vision (tracking, video detection, high‑performance pipeline), biometrics/face recognition/liveness, document understanding (scanning, OCR, augmentation, QA). Solid foundation in statistics, optimisation, supervised/self‑supervised learning and good reading comprehension of research literature. Experience working in a product environment: latency, robustness, hardware resource, security and privacy constraints. Nice‑to‑have: experience with documentary fraud, KYC, cybersecurity or digital identity; knowledge of MLOps (deployment, monitoring, CI/CD, GPU/CPU serving); participation in public benchmarks or publications; French professional proficiency; fluent English. Additional Information Contract type: Full‑time Start date: 5 January 2026 Location: Paris (remote authorised on occasion) Education level: Master’s degree Experience: > 4 years #J-18808-Ljbffr
