Machine Learning Engineer (Computer Vision & PalmCode Algorithm) - Edinburgh, On-site

Nethermind; City of Edinburgh; On-site; GBP 50,000 - 75,000; Full time

Job summary

A blockchain technology company is seeking a Machine Learning Engineer to enhance biometric security through the development of cutting-edge computer vision and ML models. You will play a pivotal role in perfecting the PalmCode biometric algorithm and collaborating with embedded systems engineers to create efficient models. Candidates should have a degree in Computer Science or Electrical Engineering and over three years of applied experience. This role offers opportunities for career growth and involves working in a diverse team.

Benefits

Global and Diverse Workforce

Learning and Development Opportunities

Career Growth and Mentorship

Access to Global Events and Conferences

Collaborative and Innovative Culture

Qualifications

• 3+ years of industry or academic experience in ML or CV.
• Experience in biometrics or embedded ML is strongly preferred.

Responsibilities

• Develop computer vision models for attack detection.
• Enhance the proprietary PalmCode algorithm.
• Design lightweight ML models for embedded devices.
• Collaborate on integrating ML within secure environments.
• Collect and clean biometric data.
• Evaluate and test models for robustness.

Skills

Computer vision expertise

Applied machine learning

Deep learning frameworks (PyTorch, TensorFlow)

Efficient model deployment

Programming in Python

Programming in C++

Strong foundations in statistics

Understanding of biometric data privacy

Education

Bachelor’s or Master’s degree in Computer Science or Electrical Engineering

Tools

TensorRT

TFLite

Arm NN

Job description

Overview

Are you the one? We are looking for a Machine Learning Engineer (Computer Vision & PalmCode Algorithm) to help us push the boundaries of biometric security. You will develop and refine computer vision and ML models for presentation attack detection, contribute to the evolution of our proprietary PalmCode biometric algorithm, and design efficient models optimized to run on embedded platforms.

This is a hands-on applied ML role — you’ll be working closely with our hardware and embedded teams to build small but powerful models that are accurate, secure, and performant in real-world environments.

Responsibilities

• Develop and improve computer vision models for presentation attack detection (spoofing, fake hands, 3D prints, etc.).
• Enhance and optimize our PalmCode algorithm for unique biometric identification.
• Design and train lightweight ML models capable of running on embedded devices with limited compute resources.
• Collaborate with security and embedded systems engineers to integrate ML inference within trusted execution environments (TEE).
• Collect, clean, and curate datasets for biometric feature extraction and spoof detection.
• Conduct model evaluation, benchmarking, and field testing to improve robustness.
• Stay up to date with research in computer vision, biometric security, and efficient on-device ML.

Skills

• Strong experience in computer vision and applied ML, ideally in biometrics, face/palm/iris recognition, or similar.
• Proficiency with deep learning frameworks (PyTorch, TensorFlow, ONNX).
• Experience building efficient models for edge/embedded deployment (quantization, pruning, distillation).
• Familiarity with presentation attack detection (PAD) methods and adversarial robustness.
• Strong programming skills in Python and C++ (experience with embedded deployment frameworks a plus).
• Solid grasp of ML lifecycle: data pipelines, training, evaluation, deployment.
• Understanding of biometric data privacy and compliance considerations.
• Very strong foundations in probability, statistics, linear algebra, and optimization, with the ability to reason about model behaviour beyond using existing libraries.

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field.
• 3+ years of industry or academic experience applying ML/CV.
• Experience in biometrics or embedded ML is strongly preferred.

Nice to have

• Experience with fine-grained recognition models (e.g., palm, fingerprint, face, voice recognition).
• Research or contributions in PAD or biometric security.
• Background in on-device inference frameworks (TensorRT, TFLite, Arm NN).
• Understanding of cryptography or secure ML (e.g., inference in TEE).
• Contributions to open-source ML/CV projects.

What we offer / Benefits

• Global and Diverse Workforce: You'll work with people from various backgrounds and cultures.
• Learning and Development: You'll work on innovative, challenging projects and have access to experts and mentors to enhance your skills.
• Career Growth: Access to training, mentorship, and opportunities to contribute to open-source initiatives.
• Global Events and Conferences: Opportunities to attend the industry events.
• Collaborative and Innovative Culture: We foster teamwork and encourage new ideas.

Our Commitment to Diversity

At Nethermind, we celebrate diversity and are committed to creating an inclusive environment for all team members. We believe a variety of perspectives drives innovation and leads to better solutions for the blockchain community.

Ready to Join Us?

If you\'re passionate about blockchain and eager to make an impact, we’d love to hear from you. Click Apply for this job to start your journey with Nethermind.