Software Engineer, ML Ops and Platform

Tools for Humanity · Munichsenior

En corto

▸Ingeniero de plataformas ML y Ops para sistemas de reconocimiento biométrico a escala global.
▸Gestiona pipelines de ML desde investigación hasta despliegue en dispositivos Edge (Orb, móvil), con monitoreo y rollback automático.
▸Destaca por construir plataformas que transforman modelos de IA de investigación en sistemas confiables en producción, en más de 17M de usuarios.

Proficiency in English is required for collaboration across global teams.

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¿Qué piden?

✓5+ años en infraestructura de ML, plataformas de datos o sistemas de ML a escala.
✓Experiencia probada en pipelines de entrenamiento, evaluación y despliegue de modelos en producción.
✓Conocimiento en CI/CD, rollouts con etapas, A/B testing y rollback en dispositivos Edge.
✓Experiencia en monitoreo en tiempo real, detección de desvío y alertas para modelos.
✓Dominio de prácticas de privacidad por diseño, seguridad y trazabilidad de datos.
✓Capacidad para colaborar con equipos de investigación, producto y firmware.

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ML pipelinesCI/CD workflowsEdge deploymentOrbOrb MiniMobile AppsTelemetry ingestionModel monitoringDrift detectionSecure APIs

¿A quién escribirle en Tools for Humanity?

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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. About the Team We are building a planet‑scale biometric recognition system that will serve more than a billion users and enable them to become part of the World protocol. 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. We are building a biometric recognition and fraud detection engine that works on the 1bn people scale. Therefore, its performance needs to outperform all the current recognition technologies. 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. To reach our next milestone—continuous, trustworthy ML innovation across millions of edge devices—we’re hiring a Senior ML Platform & Ops Engineer to own the ML lifecycle from data to device. You’ll design and operate production-grade pipelines that transform state-of-the-art ML research into deployed models with clear telemetry, rollback, and reproducibility. If you thrive on building self‑service platforms that turn research ideas into reliable, observable production systems, we’d love to meet you. Responsibilities Design, build, and operate reliable, observable infrastructure for training, evaluation, telemetry ingestion, and deployment. Maintain CI/CD workflows and automated pipelines. Edge‑aware rollout services with staged deployment, A/B experimentation and instant rollback across Orbs, Orb Mini and Mobile Apps. Develop secure APIs and backend services that expose governed datasets and model artefacts at scale. Implement automated checks, drift detection, and alerting for real-time model monitoring. Champion best practices in data lineage, reproducibility, privacy‑by‑design, security and secure edge delivery. Collaborate across ML research, product, and firmware teams to streamline delivery and feedback loops. About You 5+ years building ML infrastructure, data platforms, or production ML systems at scale.

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