Research Engineer; Research

Position: Research Engineer (Research)

Location: Greater London

Location London, United Kingdom# Research Engineer (Research) at iProov Location London , United Kingdom Salary £50000 - £65000 /year

Job Type Full-time

Date Posted January 23rd, 2026

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• Research Engineer
• About iProov
• iProov provides science-based biometric solutions that enable the world’s most security-conscious organizations to streamline secure remote onboarding and authentication for digital and physical access. Our award-winning liveness technology and iSOC offer unmatched resilience against deepfakes and generative AI threats while ensuring effortless, scalable user experiences. Trusted by leading governments and enterprises, including the U.S. Department of Homeland Security, U.K. Home Office, Gov Tech Singapore, ING, and UBS, iProov sets the standard in biometric identity assurance.

This global trust is built not only on our technology but on the strength of the people behind it. For us, diversity at iProov is about reflecting the customers we serve, holding the principles of equality and inclusion at the heart of everything we do and all that we stand for, embracing differences, creating possibilities, and growing together. We aim to foster a culture where individuals of all backgrounds feel confident in bringing their whole selves to work, feel included, and their talents are nurtured, empowering them to contribute fully to our purpose.

• The Role
• Reports to**: VP, Research
• Location**:

WeWork Waterloo, London - Hybrid

• Comp**:

Up to £65k (Base) + Company Performance Bonus (10%) + Share Options + iProov Benefits We’re looking for a Research Engineer who thrives at the cutting edge of technology, someone who doesn’t just ask questions but brings ideas, experiments, and solutions to the table. You’ll be part of a collaborative, low-ego team pushing the boundaries of liveness verification and biometric security to protect millions of users this role, you’ll spend most of your time exploring and innovating, developing new biometric tests from palm and fingerprint matching to advanced presentation-attack detection to stay one step ahead of attackers.

You’ll design acquisition systems and then stress-test them by trying to spoof and break your own work, ensuring our defences are ready before real-world threats appear.

You’ll tackle complex challenges in biometric acquisition, improve data quality, and create samples that closely mimic contact-based systems. Most importantly, you’ll anticipate and defend against threats that haven’t even been imagined yet, keeping our technology secure long after it goes live.

• How you can make an impact
• As a Research Engineer, you will use state-of-the-art Deep Learning technology to develop creative solutions for exciting, industry-defining problems.
• Take ownership of research areas in computer vision, machine learning, and biometrics.
• Work collaboratively with the research team to find the best solutions.
• Communicate research outcomes and findings across the company.
• Contribute to the broader research strategy of the team.
• Challenge the existing solutions and improve the status quo.
• Contribute to a strong team ethic, encouraging psychological safety and inclusivity
• What we would like to see from you
• A Master's or PhD in a quantitative field such as computer science, engineering, or computational neuroscience.
• Experience in machine learning and computer vision.
• Strong mathematical skills.
• Experience in developing research projects using Python.
• A solid understanding of machine learning techniques, including Neural Networks.
• Familiarity with Python libraries such as Num Py, Pandas, and Scikit-learn.
• Experience with Deep Learning libraries like PyTorch or Tensor Flow.
• The ability to process large amounts of data, including unstructured data
• Excellent communication skills for understanding and explaining complex concepts.
• Strong programming skills with a good grasp of data structures, object-oriented programming, and software engineering principles.
• Good time management and organizational skills.

Great to have (but not essential)

• Understanding of multiple machine learning disciplines, such as Image…