Senior Applied Scientist - Computer Vision

Entrust; Paris; Hybride; EUR 70 000 - 90 000; Plein temps

Résumé du poste

Entrust is seeking a Senior Applied Scientist to drive research and develop machine learning solutions focusing on digital identities. The role involves pushing research boundaries in areas such as deepfake detection and fraud detection.

The candidate will work collaboratively with teams to improve products and publish impactful research. This position is based in our Paris office with a hybrid model requiring three days in-office presence.

Join Entrust and make a difference by building cutting-edge machine learning products!

Qualifications

• Strong experience in machine learning and computer vision.
• Strong record of delivering high-performance ML-driven products.
• Deep understanding of machine learning theory.
• Strong coding skills in Python and PyTorch.

Responsabilités

• Push the frontier of research in areas such as deepfake detection and bias mitigation.
• Publish research results in conferences and journals.
• Implement bias-mitigation strategies and build fair models.
• Train and benchmark vision-language models for document extraction.
• Profile, debug and improve model training speed.
• Experiment with multimodal models to detect fraud.

Connaissances

Machine learning

Computer vision

Python

PyTorch

Outils

AWS

Encord

Ray

PyTorch Lightning

Weights & Biases

Description du poste

Get to Know Us

At Entrust, we’re shaping the future of identity centric security solutions. From our comprehensive portfolio of solutions to our flexible, global workplace, we empower careers, foster collaboration, and build solutions that help keep the world moving safely.

About the Team

You'll be joining the team leading Entrust's Identity portfolio, formerly known as Onfido (an AI-powered digital identity solution). Our technology helps businesses verify real identities using machine learning, ensuring secure remote customer onboarding. By assessing government-issued identity documents and facial biometrics using state-of-the-art machine learning, we provide companies with the assurance they need to operate securely while allowing people to access services quickly and safely.

Our Applied Scientist team consists of about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely with product engineering to deploy models to serve our worldwide customer base.

Position Overview

We are looking for a Senior Applied Scientist to design and train cutting-edge machine learning solutions related to digital identities. Join our team and work on challenging problems in deepfake detection, bias mitigation, document understanding, anomaly detection and/or efficient ML.

What you will be doing

• Push the frontier of research in areas such as deepfake detection, bias mitigation, fraud/anomaly detection, face matching, document understanding, and efficient on-device ML.
• Publish research results in national and international conferences and scientific journals. Work with product and engineering to improve our world-class identity-focused products.
• Implement bias-mitigation strategies to build fair face-matching and deepfake-detection models.
• Train and benchmark large-scale vision-language models for document extraction.
• Train a multi-modal document understanding model from scratch using synthetic data. Optimise LoRA adapter latency in PEFT/Triton.
• Profile, debug and improve model training speed on multiple GPUs.
• Experiment with multimodal models to detect fraud.

You may be a good fit if you

• Have strong experience in machine learning and computer vision.
• Have a strong record of successfully delivering high-performance ML-driven products.
• Have a deep understanding of machine learning theory.
• Have strong coding skills in Python and PyTorch.
• Care about building fair and cutting-edge machine learning products.

Strong candidates may also have

• Technical experience in one or more of the following areas: face matching, bias mitigation, anomaly detection, document understanding or on-device ML.
• Published at top-level machine learning conferences. Experience optimizing (distributed) training code.

Where you will be

This role is based in our Paris, France office and follows a hybrid model, requiring in-office presence three days per week.

Ready to Make an Impact?

If you’re excited by the prospect of working on cutting-edge machine learning for problems that matter, Entrust is the place for you. Join us in making a difference. Let’s build a more secure world—together.