Director Of Ai Platform (All Genders)

Experteer Overview As Director of AI Platform, you will define and drive the strategy for Glovo’s unified ML and AI platform, enabling global teams to leverage AI at scale.You will partner with executives and cross-functional leaders to align platform capabilities with business goals, shaping an end-to-end MLOps environment and fostering a high-performing engineering culture.You’ll own the platform’s roadmap, drive innovation and efficiency, and build trust through measurable reliability and impact.This is a chance to lead a strategic platform that accelerates AI adoption across a globally distributed organisation.Compensaciones / Beneficios- Define vision, strategy, and roadmap for the unified ML/AI platform aligned with business and tech goals- Lead development of an end-to-end MLOps platform, target architecture, tech stack, and operating model- Promote robust MLOps practices and monitor KPIs/SLOs for reliability, performance, cost, and user satisfaction- Build, mentor, and scale high-performing cross-functional teams- Partner with global stakeholders to understand ML needs, secure buy-in, and drive adoption of platform standards- Manage cost, vendor relations, and capital/operational expenditure related to the platformResponsabilidades- 10+ years in data u** ML leadership within high-growth tech- Hands-on design/operation of MLOps platforms- CI/CD for ML, deployment pipelines, monitoring, feature stores, scalable serving- End-to-end ML lifecycle and common ML techniques- Familiar with hyperscaler MLOps offerings- DevOps principles and CI/CD tooling- Infrastructure as code, Docker, and Kubernetes- 5+ years in leadership with globally distributed teams- Ability to connect ML initiatives to business outcomes and lead organization-wide change- Understanding of ML challenges in multi-subsidiary global organizationsRequisitos principales-

10+ years in data u** ML leadership within high-growth tech

• Hands-on design/operation of MLOps platforms
• CI/CD for ML, deployment pipelines, monitoring, feature stores, scalable serving
• End-to-end ML lifecycle and common ML techniques
• Familiar with hyperscaler MLOps offerings
• DevOps principles and CI/CD tooling
• Infrastructure as code, Docker, and Kubernetes
• 5+ years in leadership with globally distributed teams
• Ability to connect ML initiatives to business outcomes and lead organization-wide change
• Understanding of ML challenges in multi-subsidiary global organizationsRequisitos principales