Machine Learning Engineering Manager (Face Intelligence)

At Veriff, we’re building the foundational trust layer of the internet — and Face Intelligence sits at the core of that mission. This role is about building state-of-the-art Machine Learning models that power Identity Verification at global scale, with a sharp focus on Face Biometrics, Liveness Detection, and resilience against rapidly evolving threats like deepfakes and synthetic identities.

We’re looking for an experienced Engineering Manager to lead our Face Intelligence team with a strong focus on Data Science and Machine Learning. This team owns the end-to-end lifecycle of biometric models — from research and training, to evaluation, deployment, and continuous improvement in production. The work directly impacts authentication accuracy, fraud prevention, and user trust across millions of verifications worldwide.

You’ll lead a high-performing team of data scientists and ML engineers building Computer Vision and Machine Learning systems for Facial Biometrics. Working closely with Product, ML Platform, Fraud Prevention, and Legal, you’ll ensure our models deliver high accuracy, scale reliably, respect privacy, and remain resilient as threats evolve.

Join us if you’re excited about pushing the boundaries of applied machine learning, building production-grade biometric systems, and turning cutting-edge research into real-world impact.

You’ll help us protect honest people online by:

• Leading, growing, and developing a high-performing team of data scientists and ML engineers responsible for face biometrics and liveness detection models.
• Defining the team's structure and evolution as it scales, introducing strong research-to-production practices, clear ownership, and measurable outcomes.
• Owning the end-to-end delivery of biometric ML systems — from data strategy and model training to evaluation, deployment, monitoring, and iteration in production.
• Driving the development of state-of-the-art face recognition, face liveness, and anti-spoofing models, with a strong focus on robustness, generalization, and fairness across geographies and demographics.
• Partnering closely with Product, Authentication, Identity, and Fraud teams to translate verification, authentication, and fraud prevention problems into well-defined ML objectives, metrics, and roadmaps.
• Working with ML Platform teams to ensure efficient training pipelines, scalable inference, strong observability, and continuous monitoring of model performance and drift.
• Ensuring regulatory compliance, data privacy, and responsible AI practices are embedded into how models are designed, trained, and evaluated.
• Building a team culture centered on scientific rigor, experimentation, collaboration, and high-quality execution.
• Contributing to Veriff's long-term biometric strategy by anticipating and defending against emerging threats such as deepfakes, replay attacks, and generative AI–based fraud.
• Mentoring senior data scientists and ML engineers, supporting their technical growth and leadership development.

You are the right future Veriffian for the job if:

• You bring strong technical leadership in machine learning, computer vision, or applied data science, and enjoy working close to complex real-world problems.
• You’ve led teams building and operating production ML systems end-to-end, including model training, evaluation, deployment, and post-deployment monitoring.
• You’re comfortable in high-growth environments and know how to scale both teams and ML systems without sacrificing quality.
• You balance technical depth with people leadership, and can guide teams through ambiguity while setting clear direction.
• You’re excited to work in a regulated domain and collaborate with legal and compliance partners to build privacy-first, responsible AI systems.

You’re an especially awesome match if you have:

• Hands-on experience in biometrics, computer vision, or face-related ML problems such as face recognition, liveness detection, or anti-spoofing.
• Deep familiarity with modern ML frameworks and embedding-based architectures used in large-scale biometric systems.
• Experience designing evaluation frameworks, datasets, and metrics for highly imbalanced, adversarial, or safety-critical ML problems.
• Exposure to regulated industries (identity verification, fintech, security, healthcare) and a solid understanding of data protection and consent principles.
• Strong systems thinking — you can design ML solutions that deliver short-term wins while building durable long-term differentiation.

• Flexibility to work from home
• Stock options that ensure your share in our success
• Extra recharge days on top of your annual vacation
• Comprehensive relocation support to Estonia or Spain
• Extensive medical, dental, and vision insurance to ensure you’re feeling great physically and mentally
• Learning and Development & Health and Sports budget that you are free to tailor to your own needs
• Four weeks of fully paid sabbatical leave after reaching your 5th work anniversary