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# Applied Scientist Lead - Computer Vision

- **Company:** Entrust
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Computer Vision, Data Mining, Python (Programming Language), Machine Learning, Language Modeling, Pytorch, Software Coding
- **Published:** September 24, 2026
- **Apply:** https://www.totaljobs.com/job/lead/entrust-job108029289

## About the Role

* 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.

## Description

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'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.


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