Director, Machine Learning Platform

• Lead the vision, strategy, and roadmap for Delivery Hero's unified ML platform, aligning it with business, product, and global tech goals
• Communicate this strategy and its value to your users and stakeholders, including executives
• Stay informed on MLOps and AI/ML trends like Generative AI
• Oversee the creation and continuous improvement of a comprehensive, end-to-end MLOps platform and its target architecture, technology stack, and operational model
• Evangelize robust MLOps practices
• Establish and monitor key performance indicators (KPIs) and Service Level Objectives (SLOs) for platform reliability, scalability, performance, cost-effectiveness, and internal customer satisfaction
• Build, lead, mentor, coach, and inspire high-performing teams
• Cultivate a world-class engineering culture centred on innovation, collaboration, technical rigour, ownership, agility, and continuous learning
• Attract, hire, develop, and retain top-tier talent
• manage team performance, provide career growth pathways, and build leadership capacity within your organisation
• Serve as a primary technology partner to key stakeholders globally and deeply understand their current and future ML needs
• Proactively influence cross-functional teams and senior leadership to drive alignment, secure buy-in, and promote the adoption of platform capabilities, standards, and best practices
• Meet immediate stakeholder demands while building for long-term scalability and maintainability
• Ensure efficient allocation of capital and operational expenditures, and drive cost optimisation initiatives
• Oversee relationships with key technology vendors and partners where applicable

• 10 years of experience in Data & ML leadership within high-growth tech
• Specializes in hands-on design and operation of MLOps platforms
• Expertise includes CI/CD for ML, deployment pipelines, monitoring, feature stores, and scalable serving
• Proficient in the end-to-end ML lifecycle and common ML techniques
• Familiar with major hyperscaler MLOps offerings
• Strong understanding of DevOps principles and CI/CD tooling
• Experience with infrastructure-as-code, Docker, and Kubernetes
• 5+ years in leadership positions leading cross-functional, globally distributed teams and initiatives
• Able to inspire large technical teams and stakeholders with a compelling vision and long-term strategy connecting ML initiatives to business outcomes
• Ability to lead, influence, and execute, paired with strong stakeholder management
• History of driving organizational change and adoption of new technologies
• Understanding of ML challenges within global organizations operating multiple subsidiaries

Expertise in recent advancements in AI, particularly LLMs, RAG, and associated frameworks, is a strong plus.