Senior Applied Scientist - Computer Vision

Entrust
City of London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Technology Specialist - AI

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Join us at Entrust

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.


Get to Know Us

Headquartered in Minnesota, Entrust is an industry leader in identity-centric security solutions, serving over 150 countries with cutting-edge, scalable technologies. But our secret weapon? Our people. It’s the curiosity, dedication, and innovation that drive our success and help us anticipate the future.


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.


Representative work:

  • 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.
  • Create a large-scale dataset for deepfake detection.
  • 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 optimising (distributed) training code.



Where you will be: This role is based in our London, UK office and follows a hybrid model, requiring in-office presence three days per week.


Benefits UK

  • 25 days annual leave plus a day off for your Birthday.
  • Two paid volunteering days per year.*
  • Bupa Private Medical and Dental Insurance*
  • Pension with The People’s Pension (employer contribution 4% of base salary)*
  • Generous paid parental leave
  • Life enrichment allowance of up to £80 per month to use for services including gym, yoga, fitness classes, massages, childcare, and therapy
  • Dedicated learning opportunities including using tools like Linkedin Learning with availability to use for learning resources such as books, coaches, conferences, courses, podcasts, and more
  • Our open and transparent culture is reflected in our “Better Together” motto and we bring this to life by meeting once a week for our global weekly roundup (OnThursday); holding quarterly team socials, and other company-wide social events
  • Expense up to £300 (or local equivalent) to purchase workstation setup equipment
  • The opportunity to become a member of Entrust’s resource groups in order to learn different skills in our belonging groups


Ready to Make an Impact?

If youʼre 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. Letʼs build a more secure world—together.


Apply today!


NO AGENCIES, NO RELOCATION


#LI-GR1

#ENT123

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.