Director, Machine Learning Engineering - Surfaces Foundation

About

This leadership role sits at the core of large-scale personalization systems that define how hundreds of millions of users experience recommendations across digital surfaces. You will guide the evolution of foundational machine learning platforms that power targeting, ranking, serving, and evaluation systems at massive scale. The role blends deep technical leadership with strategic platform thinking, ensuring teams can innovate quickly while relying on stable, shared infrastructure. You will work across multiple engineering, product, and data science groups to align priorities and shape long-term architectural direction. A key focus will be enabling scalable AI-driven systems and promoting the effective adoption of modern development tools across teams. This is a high-impact position where your decisions directly influence user experience, system performance, and the future of personalization technology.

Accountabilities

• Lead engineering managers and ML engineering teams building platform systems for large-scale personalization and recommendation use cases
• Define and evolve the technical vision for core machine learning infrastructure, including targeting, serving, evaluation, and agent-based systems
• Establish platform capabilities that balance shared infrastructure with product team autonomy and speed of execution
• Drive incremental evolution of ML platforms, ensuring continuous delivery and avoiding disruptive system rewrites
• Partner with product, data science, and engineering leadership to align priorities across multiple squads and initiatives
• Contribute to architectural decisions and resolve complex technical challenges in production environments when needed
• Promote and guide the adoption of AI-assisted development tools across engineering teams
• Recruit, develop, and mentor engineering leaders and contributors, fostering a strong and inclusive culture

Requirements

• Extensive experience building and scaling machine learning systems in large-scale consumer-facing products
• Strong background in recommendation systems, ranking systems, or content delivery platforms with full ML lifecycle understanding
• Proven ability to lead platform engineering teams and define long-term technical strategy
• Strong platform mindset with the ability to balance centralized infrastructure and product-level autonomy
• Experience working with modern AI tools and integrating them into engineering workflows
• Demonstrated leadership in driving organizational or technical transformation initiatives
• Strong cross-functional collaboration skills across engineering, product, and data science teams
• Ability to navigate ambiguity and make strategic trade-offs between short-term delivery and long-term scalability
• Commitment to building inclusive, high-performing engineering cultures and developing talent

Benefits

• Flexible remote work within the EMEA region
• Opportunity to work on large-scale machine learning systems impacting global user experiences
• Strong emphasis on career growth and leadership development
• Collaborative, cross-functional international environment
• Exposure to cutting-edge AI and personalization technologies
• Inclusive and supportive team culture focused on learning and innovation
• Flexibility aligned with Central European and GMT collaboration hours