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

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 / document spoofing
  • 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

• Minimum 4 years of experience in deep learning applied to computer vision, with a portion 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)
  • 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.

Nice‑to‑Have

• Experience in documentary fraud, KYC (Know Your Customer), cybersecurity, or digital identity.
• 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).

Additional Information

• Contract Type: Full‑Time
• Start Date: 31 July 2026
• Location: Paris
• Education Level: Master's Degree
• Experience: > 4 years
• Occasional remote authorized