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,
  • 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.