Director, Machine Learning Platform (all genders)

As the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We operate in over 70+ countries worldwide, powered by tech, designed by people. As one of Europe’s largest tech platforms, headquartered in Berlin, Germany. Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index. We enable creative minds to deliver solutions that create impact within our ecosystem. We move fast, take action and adapt. No matter where you're from or what you believe in, we build, we deliver, we lead. We are Delivery Hero.

We are looking for a Director, Machine Learning to lead our ML Platform domain within the Data & Platform tribe. The position will be based in our Barcelona hub and will be responsible for defining a compelling vision, shaping the strategy, and driving the execution for Delivery Hero’s unified Machine Learning platform and establishing an MLOps culture. This highly strategic position requires gaining buy-in from senior stakeholders and driving implementation across diverse business units, and will be instrumental in empowering teams across Delivery Hero to leverage AI effectively.

This role demands a leader with exceptional technical depth across machine learning domains, combined with strategic foresight and proven stakeholder management experience in a globally distributed organisation. Success in this role is measured by the increase in innovation velocity, efficiency, and satisfaction of teams leveraging the ML platform.

Your Mission:

Reporting to the Senior Director Data Platform, you will be responsible for leading and scaling the ML Platform domain. Your key responsibilities will include:

Strategic Leadership

• 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.

  
  
  

Platform Development & Operations

• 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.

  
  
  

People Management

• 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.

  
  
  

Stakeholder Management

• 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

  
  
  

Cost Management

• Ensure efficient allocation of capital and operational expenditures, and drive cost optimisation initiatives.

  
  
  

• Oversee relationships with key technology vendors and partners where applicable.

  
  
  

Technical Experience

• 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.

  
  
  

Leadership Experience

• 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

  
  
  

Industry Knowledge

• 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.