Principal / Staff Machine Learning Engineer — Biometrics & Anti-Spoofing

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Our client is a global technology company specializing in biometric identity verification, fraud prevention, and AI-powered security. They are seeking a Principal/Staff Machine Learning Engineer to lead the development of advanced biometric security and anti-spoofing solutions, focusing on Presentation Attack Detection (PAD) and Injection Attack Detection (IAD). This hands-on role combines deep learning research, architecture ownership, and production engineering, with significant technical autonomy and influence over product strategy. The position offers remote flexibility, with a preference for candidates based in Lisbon or open to an international working environment.

• Design, train, and deploy deep learning models for face liveness detection, PAD, IAD, and deepfake detection.
• Develop state-of-the-art approaches to counter adversarial threats, including generative AI models, 3D masks, and face-morphing attacks.
• Own the full ML lifecycle, from data strategy and model architecture to training infrastructure, evaluation, and production deployment.
• Build and optimize ML solutions for web, mobile (Android/iOS SDKs), and server-side environments.
• Define robust evaluation methodologies and support preparation for independent testing and certification (e.g., iBeta, BixeLab, NIST FRVT, ISO/IEC 30107-3).
• Optimize models for low-latency inference, mobile and edge deployment, and adversarial robustness.
• Stay at the forefront of research in face anti-spoofing, deepfake detection, and adversarial ML, translating advances into production.