Director of AI & Biometrics

About the Company

Tools for Humanity (TFH) designs and builds technology behind World. World is building a real human network designed to accelerate people in the age of AI. The TFH and World tech stacks make this possible through the Orb, World ID, and World App, adding a human layer to an AI-driven internet.

Responsibilities

• Own the vision, roadmap, and execution for World’s biometric recognition stack, including iris/face recognition and fraud defenses
• Lead the end-to-end ML system lifecycle including data acquisition, pipelines, training, evaluation, and deployment
• Define performance goals balancing biometric accuracy, user experience, and fraud resistance
• Establish engineering and scientific standards for reproducible experimentation and MLOps discipline
• Partner with hardware, product, and security teams to ensure tight integration between sensing and inference
• Attract, develop, and coach a diverse team of experts and lead organizational scaling
• Represent biometrics leadership internally to communicate trade-offs, risks, and progress

Requirements

• Strong science or engineering background in computer vision, machine learning, robotics, or signal processing
• Demonstrated experience with the full ML lifecycle from data to deployment and monitoring
• Proven ability to deliver production-grade ML systems on mobile devices or performance-constrained environments
• Significant experience leading engineering or applied research teams
• Demonstrated ability to lead cross-functional efforts across product, engineering, and research
• Strong people leadership skills including mentoring, hiring, and performance management
• Excellent communication skills for aligning cross-functional partners

Preferred Qualifications

• Domain expertise in iris recognition and/or face recognition
• Experience with presentation attack detection (PAD) and biometric fraud prevention
• Familiarity with privacy-enhancing technologies like secure enclaves, TEEs, or differential privacy
• Experience operating ML systems at very large scale under strict compliance requirements