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.

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-abstract 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

Job 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);
  • 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.

Recruitment Process

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: 30 September 2026
• Location: Paris
• Education Level: Master’s Degree
• Experience: > 4 years
• Occasional remote authorized