Director of AI & Biometrics(m/w/x)

Requirements

• Strong science and/or engineering background (e.g., computer vision, machine learning, robotics, signal processing, or related field)
• Ability to evaluate and guide research and engineering decisions
• Experience with modern and traditional computer vision / ML
• Deep understanding of ML full lifecycle (data, training, deployment, monitoring, iteration)
• Ability to deliver production-grade ML systems
• Deployment on mobile devices and/or performance-constrained environments
• Experience with custom hardware (strong plus)
• Significant experience leading engineering and/or applied research teams
• Setting direction, prioritization, and execution in complex environment
• Ability to lead cross-functional efforts (product, engineering, research, operations)
• Strong people leadership (management, mentoring, hiring, performance management, scaling teams)
• Comfort operating at multiple levels (strategy, architecture, metrics, technical problem-solving)
• Excellent communication skills
• Ability to align cross-functional partners
• Ability to explain technical decisions to varied audiences
• Domain expertise in iris recognition and/or face recognition
• Evaluation methodologies and real-world failure modes (iris/face recognition)
• Experience with presentation attack detection (PAD)
• Biometric fraud prevention / adversarial robustness
• Familiarity with privacy-enhancing technologies
• Privacy-by-design approaches for biometric systems (e.g., secure enclaves/TEEs, on-device processing, cryptographic approaches, differential privacy, federated learning, secure aggregation)
• Experience operating ML systems at very large scale
• Operating ML systems under strict compliance requirements

Tasks

• Lead the biometric recognition technology team.
• Ensure reliable and secure biometric systems at scale.
• Build and scale high-performing teams.
• Set technical direction for biometric ML systems.
• Define execution strategy for biometric ML systems.
• Oversee data collection and governance.
• Oversee dataset curation and pipelining.
• Oversee model training and evaluation.
• Oversee deployment on mobile and custom hardware.
• Oversee production monitoring and rapid iteration.
• Collaborate with product, security, hardware, and operations teams.
• Deliver high-performing, privacy-preserving biometric systems.
• Ensure systems are robust against fraud and presentation attacks.
• Meet agreed milestones and delivery timelines.
• Own biometric stack vision, roadmap, and execution.
• Balance research innovation with production reliability.
• Lead data acquisition strategy and quality standards.
• Lead data pipelines and dataset governance.
• Lead training, evaluation, and benchmarking at scale.
• Lead deployment and optimization for mobile/custom hardware.
• Lead monitoring, regression detection, and incident response.
• Lead fast iteration loops for ML systems.
• Define and drive performance goals.
• Balance biometric accuracy, user experience, and fraud resistance.
• Utilize metrics, benchmarks, and production feedback.
• Establish strong engineering and scientific standards.
• Ensure reproducible experimentation and code quality.
• Foster a testing and review culture.
• Implement MLOps discipline and documentation.
• Partner on technical vision and strategy.
• Ensure tight integration across sensing and backend systems.
• Attract and develop diverse expert teams.
• Coach expert teams of varying seniority.
• Create clear career paths and feedback loops.
• Foster a culture of ownership and excellence.
• Foster a collaborative environment.
• Lead hiring and team design.
• Lead organizational scaling for growth.
• Represent biometrics leadership internally.
• Act as primary contact for company leadership.
• Communicate trade-offs, risks, and progress.
• Drive alignment across all stakeholders.

Work Experience

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