Machine Learning Engineer – Deepfake & Injection Attack Detection, Face Liveness

Role Overview

• Design, train, and deploy machine learning models for image-based fraud detection, including deepfake detection, injection attack detection, and digital manipulation analysis in biometric verification
• Work end-to-end across the ML lifecycle: dataset curation, model development and training, evaluation and iteration using fraud-relevant metrics, and production deployment and monitoring
• Build robust data pipelines, including data validation, cleaning, and labeling strategies
• Define and execute evaluation frameworks focused on real-world performance

Requirements

• Bachelor’s degree in Computer Science, Engineering, or related field
• 2+ years of experience deploying machine learning models into production
• Strong background in computer vision (image-based ML)
• Solid programming skills in Python
• Hands-on experience with PyTorch and/or TensorFlow
• Experience working with real-world datasets and building data pipelines

Tech Stack

• Python
• PyTorch
• Tensorflow

Benefits

• Competitive package
• Full Remote contract
• Annual Leave
• Home Office Allowance
• Annual Bonus – up to 10%
• Health Insurance
• Learning & Development: We promote continuous learning and support role-aligned development opportunities, with access to a complimentary LinkedIn Learning licence.