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

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