Lead Applied Scientist - Computer Vision

Entrust Identity Verification — Powering the systems behind digital trust.

At Entrust, identity is no longer a compliance checkbox—it’s a real-time product problem shaped by machine learning, adversarial behavior, and high-stakes decisions. Every verification is a trade-off between fraud prevention, user experience, speed, and trust—and getting it right determines whether a legitimate user gets access or a sophisticated attacker gets stopped.

Our Identity portfolio (formerly Onfido) powers document and biometric verification, fraud detection, and identity decisions at global scale. From detecting deepfakes to enabling seamless onboarding, our ML systems sit directly on the critical path of digital trust—used by banks, fintechs, marketplaces, and enterprises worldwide.

About the Team:

You’ll join a high-caliber Applied Science group (~20+ scientists) working at the intersection of machine learning, product, and real-world constraints. The team is supported by a state-of-the-art ML Ops ecosystem (AWS, Encord, Ray, PyTorch Lightning, Weights & Biases) and partners closely with product and engineering to ship models into production at scale. This is applied research in its truest sense: advancing the frontier while delivering systems that must be accurate, fast, fair, and resilient in adversarial environments. The team is supported by a state-of-the-art ML Ops ecosystem (AWS, Encord, Ray, PyTorch Lightning, Weights & Biases) and a massive proprietary dataset of images and videos. The team partners closely.

Position Overview:

We’re looking for an Applied Scientist Lead  - Computer Vision to lead one of our Applied Science teams at Entrust. You will lead a team of 6 applied scientists that trains and evaluates vision-language models for data extraction on one side, and efficient models (<5MB) that run on mobile devices on the other. The ML space here is exciting: better vision-language models enable better and more general extraction, and techniques like distillation and quantisation allow models to become smaller and smaller. We expect this role to be hands-on for about 50% of your time—making contributions to the codebase helps you deliver better feedback as well.

What you will be doing:

• Define the team's roadmap together with product and engineering leads.
• Stay up-to-date on the vision-language modelling and efficient ML literature, and translate these insights into product opportunities.
• Manage a team of 6 Applied Scientists.
• Contribute to the regular development lifecycle by contributing to dataset creation, model training and evaluation code.
• Push the frontier of research in areas such as vision-language modelling, document understanding, few-shot learning, distillation, quantisation, and active learning.
• Publish research results in national and international conferences and scientific journals.

You may be a good fit if you:

• Have 2+ years of experience leading a team of ML scientists or research engineers.
• Have 5+ years of industry experience as an individual contributor in a machine learning science team, either as an ML scientist or research engineer.
• 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.

Strong candidates may also have:

• Technical experience in one or more of the following areas: document understanding, vision-language modelling, few-shot learning, distillation, quantisation and active learning.
• Published at top-level machine learning conferences.
• Experience optimizing (distributed) training code.

What are we looking for?

an Applied Scientist Lead excels in three areas:

1. Scientific Contributions: This person must shine as an example through past work and scientific drive within the team. They will continue to make direct contributions through side projects and, more often, by influencing the team’s work with unique ideas. The goal of our team is also to positively impact the broader community, so this person should stand out through external contributions such as publications, talks, and open-source work.

2. Leadership & People Management: This person must be passionate about growing the people on their team. Applied Scientists often require dedicated and thoughtful support due to the inherently unpredictable nature of their work.

3. Product and Business Acumen: We are a product-centric and customer-centric company, so our work should strive to deliver meaningful product impact. This person must deeply care about both the product and the business, and excel at building long-lasting relationships across cross-functional teams including Product, Design, Engineering, and Analytics.

Where you will be: London, UK or Paris, France (Hybrid – 3 days in office)

Why join us? Solve problems that matter—at scale.

At Entrust, we combine cutting-edge research with a deeply product-oriented culture—where ideas don’t stop at papers, they power systems used by millions. Our products sit on the front lines of digital trust, tackling visual fraud at scale—from deepfakes and synthetic identities to sophisticated spoofing attacks.

You’ll lead teams, shape ML direction, and build models that must perform in the real world—under adversarial conditions, across global systems, and with real consequences. If you’re motivated by turning advanced research into production-grade systems—and pushing the frontier while doing it—this is the kind of work worth doing.

Apply today!

NO AGENCIES, NO RELOCATION

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For US roles, or where applicable:

Entrust is an EEO/AA/Disabled/Veterans Employer

For Canadian roles, or where applicable:

Entrust values diversity and inclusion and we are committed to building a diverse workforce with wide perspectives and innovative ideas. We welcome applications from qualified individuals of all backgrounds, and we strive to provide an accessible experience for candidates of all abilities.

If you require an accommodation, contact accessibility@entrust.com.

Recruiter:

Grace Rusingiza

Grace.Rusingiza@entrust.com