About us

Signaturit Group is a leading SaaS software company, specializing in LegalTech. We are the European champions of unified digital transaction management, helping hundreds of thousands of clients in 180 countries authenticate and manage their digital identity, handle client onboarding and KYC (Know Your Customer), electronically sign documents, and securely archive critical transactions.

In France, you may know us as Universign (for electronic signatures) and VIALINK (for client onboarding and KYC).

Today, more than 400 experts and passionate professionals, based in Paris, Barcelona, Valencia, and Madrid, are working every day towards our shared success.

Context Overview 🔎

At Vialink, now part of the Signaturit Group, our mission is to simplify and secure our clients’ digital journeys. We automate and secure critical client interactions such as onboarding, customer verification, and contract signing. As part of a scale-up in the RegTech space, we develop SaaS solutions specialized in digital identity security, electronic signatures, and fraud prevention. Our Vialink 360 platform enables businesses to enhance their client experience with solutions in:

- Electronic Signature: digitization and automation of signing processes

- KYC & ID Verification: online identity and document verification with AI and machine learning

What you will do at Signaturit 🚀

VIALINK’s AI Lab develops and maintains models which run in production for our client needs like document image classification and document Object detection, name entity recognition and so on...

The main role of the candidate is to explore the state of the art and build a fraud detection model focused on fraud detection in ID cards.
The internship will last 6 months.

Your missions :

• State of art literature
• Experiment with methods which are already mentioned in the literature and adapt them to fit our problem
• Fine-tune the selected model
• Evaluate accuracy and performance of the model
• Evaluate the results and identify the root of possible issue
• Conduct the research with a private internal dataset
• English language ( reading and writing skills)
• Final year of study
• Knowledge of machine learning concepts and algorithms (Classification and regression concepts)
• Knowledge of at least one deep learning architecture (e.g. CNN, U-Net, Auto-Encoders, Transformers)
• Knowledge of classic image processing techniques (e.g. filtering, edge detection, morphological operations)
• Python programming language
• Solid skills in linear algebra and statistics
• Knowledge of one machine learning / deep learning framework : Tensorflow / Keras, Pytorch, scikit-learn
• Discovery Call (30 min)
• Technical tests online
• Technical interview
• 🍽️ Restaurant card
• 🚅Sustainable Mobility Package