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. As bots and autonomous agents reshape the internet, people, institutions, and applications need a trusted way to confirm who is a real human while preserving privacy. The TFH and World tech stacks make this possible: the Orb verifies real, unique people, World ID proves it privately, and World App puts these capabilities, and more, in people’s hands. Together, they add a human layer to an AI-driven internet.
World is already running at a global scale. More than 17 million people across 160 countries have verified with World ID, and more new Orb verifications take place each week. World App is already among the most used wallets globally. Developers are integrating World ID to build safer online experiences and create spaces where real people can participate, earn, and be recognized in ways AI simply can’t replicate.
Founded in 2019, TFH has more than 400 people across hardware, software, AI, cryptography, mobile engineering, and global operations. Our teams come from OpenAI, Tesla, SpaceX, Apple, Google, Stripe, Meta, Coinbase, Palantir and MIT Media Lab. We’re backed by leading investors, including a16z, Khosla Ventures, Bain Capital Crypto, Blockchain Capital, Variant, Tiger Global, and Coinbase Ventures, as well as prominent operators and founders across fintech and AI.
TFH and World have been featured on the cover of TIME Magazine, highlighted in Fast Company’s Next 5 in Fintech, and explored in a Bloomberg deep dive. The New York Times, Bankless and TechCrunch have all recognized our collective progress in identity, cryptography, AI, and global-scale hardware deployment. Our leadership is also named to the Time AI 100. Learn more about the newest product launches from our Liftoff event.
The AI & Biometrics team is building a biometric recognition system that delivers an unprecedented level of accuracy at a billion people scale. We use cutting-edge machine learning models deployed on custom hardware to enable high-quality image acquisition, identification, and fraud prevention, all while requiring minimal user interaction.
Operating at this scale places our team at the frontier of biometric recognition. Our systems must deliver production-grade accuracy, latency, robustness and security beyond what existing recognition technologies can support today. We leverage our powerful custom-made iris recognition and presentation attack detection device, the Orb, combined with the latest research from the field of AI and Deep Learning.
Our team is committed to building systems that respect user privacy by design. Our approach to identity leverages cryptographic principles and privacy-preserving verification techniques so that biometric data is processed locally and used only to generate secure, non-linkable proofs of identity, ensuring users retain control and choice over their personal information
As Director of Biometrics, you will lead the team responsible for the core biometric recognition technology behind the World project - especially iris and face recognition, and the systems that make these technologies reliable and secure at massive scale.
You will set the technical direction and execution strategy across the full lifecycle of biometric ML systems: data collection and governance, dataset curation and pipelining, model training and evaluation, deployment (including mobile and custom hardware), monitoring in production, and rapid iteration. You will partner closely with product, security, hardware, and operations teams to ensure that our team delivers high-performing, privacy-preserving biometric systems that are robust against fraud and presentation attacks, meeting agreed milestones and delivery timelines.
This is a leadership role for someone who can combine strong scientific and engineering judgment with pragmatic delivery, and who enjoys building and scaling high-performing teams—from our current group of ~20 people, with plans to roughly double in size by the end of the year.
This role is onsite 5 days/week and sits in our Munich office.
Own the vision, roadmap, and execution for World’s biometric recognition stack (iris/face recognition and related fraud defenses), balancing research innovation with production reliability
Lead the end-to-end ML system lifecycle:
data acquisition strategy and quality standards
data pipelines and dataset governance (privacy, access control, lineage, compliance)
training, evaluation, and benchmarking at scale
deployment and optimization for mobile devices and custom hardware
monitoring, regression detection, incident response, and fast iteration loops
Define and drive performance goals that balance biometric accuracy, user experience, and fraud resistance, using clear metrics, benchmarks, and production feedback loops.
Establish strong engineering and scientific standards: reproducible experimentation, code quality, testing, review culture, MLOps discipline, and documentation
Partner on the technical vision and strategy with hardware, product, and security teams to ensure tight integration between sensing, image acquisition, on-device inference, and backend systems
Attract, develop and coach a diverse team of experts with different levels of seniority ; create clear career paths, feedback loops, and a culture of ownership and excellence. Foster a collaborative environment for brainstorming, advising, and knowledge sharing.
Lead hiring, team design, and organizational scaling from today’s team size toward next year’s growth plan
Represent biometrics leadership internally as the primary point of contact for company leadership, clearly communicating trade-offs, risks, and progress, and driving alignment across all stakeholders.
Strong science and/or engineering background (e.g., computer vision, machine learning, robotics, signal processing, or related field), with the ability to evaluate and guide both research and engineering decisions
Demonstrated experience with modern and traditional computer vision / ML, and a deep understanding of the full lifecycle: data training deployment monitoring iteration
Proven ability to deliver production-grade ML systems, including deployment on mobile devices and/or performance-constrained environments; experience with custom hardware is a strong plus
Significant experience leading engineering and/or applied research teams of meaningful size, including setting direction, prioritization, and execution in a complex environment
Demonstrated ability to lead cross-functional efforts across product, engineering, research, and operations.
Strong people leadership: management, mentoring, hiring, performance management, and scaling teams
Comfort operating at multiple levels - from strategy, architecture and metrics down to helping unblock critical technical problems
Excellent communication skills: able to align cross-functional partners and explain technical decisions to varied audiences
Domain expertise in iris recognition and/or face recognition, including evaluation methodologies and real-world failure modes
Experience with presentation attack detection (PAD) and broader biometric fraud prevention / adversarial robustness
Familiarity with privacy-enhancing technologies and privacy-by-design approaches for biometric systems (e.g., secure enclaves/TEEs, on-device processing patterns, cryptographic approaches, differential privacy, federated learning, secure aggregation, etc.)
Experience operating ML systems at very large scale and under strict compliance requirements
