Senior Director of Machine Learning Engineering

About the Role

The CVO Tribe at HelloFresh manages two of the company's key financial drivers: benefit optimization and pricing. Leveraging machine learning, personalization, and lifetime value prediction, the tribe replaces traditional manual rules-based decisions with advanced data-driven solutions. The engineering team is internationally distributed across Berlin, Warsaw, NYC, Boulder, and Toronto and integrates Frontend, Backend, Data, and ML Engineering alongside embedded Data Scientists. The work encompasses a diverse blend of ML-heavy systems for benefit recommendations, personalization, and customer lifetime value forecasting, coupled with backend and distributed systems that support pricing infrastructure and subscription products at scale.

As the Senior Director based in Berlin, you will guide this broad technical scope by setting strategies for ML, backend, and data disciplines across multiple time zones, without the reliance on daily on-site presence.

Key Responsibilities

• Lead and coordinate a team of 25-30 engineers, data scientists, and ML specialists distributed across Berlin, Warsaw, NYC, Boulder, and Toronto through Engineering Managers and Staff Engineers.
• Define and oversee the ML strategy related to benefit recommendation, personalization, and customer lifetime-value prediction, alongside backend and distributed systems approaches for pricing and subscription architecture.
• Spearhead the evolution of workflows into fully GenAI-native, cross-functional product squads, enhancing teams already highly proficient in AI-assisted code delivery.
• Ensure excellence in system reliability and operations including observability from model predictions to customer impact, implementing SLIs/SLOs, incident response, and robust MLOps methods such as model retraining, rollback, and experimental tracking.
• Collaborate closely with Product, Data Science, Marketing, Finance, and other engineering teams to align technical priorities with strategic business goals.
• Manage and mentor Engineering Managers and Data Science Leads across various disciplines and global locations, ensuring team well-being, delivery performance, and adherence to engineering standards.

Required Qualifications and Expertise

• Broad proficiency in both ML and backend engineering, with strong credibility in each to effectively guide production ML systems and collaborate with Data Science, plus deep understanding of distributed systems that underpin pricing and subscription services.
• Extensive leadership experience managing globally dispersed teams across multiple nations and time zones, adept at balancing US-European work hours and comfortable with regular travel.
• Advanced expertise in ML engineering including feature engineering, training and serving infrastructure, experimentation platforms, and MLOps. Experience with causal inference or uplift modeling is advantageous.
• Deep knowledge of distributed backend systems, including scalable backend services and data pipelines in high-throughput, revenue-critical operational environments; experience with subscription or billing systems is a plus.
• Proven record of AI-native leadership, involving adoption and scaling of AI-centered engineering practices beyond mere use of AI tools.
• Strong commercial and pricing domain knowledge or a quick learner in these areas with focus on benefit optimization, lifetime value forecasting, and pricing elasticity.
• At least 12 years of software and ML engineering experience, with a minimum of 5 years overseeing Engineering Managers responsible for multiple technical disciplines across multiple geographic locations.
• Commitment to operational excellence with a solid foundation in Site Reliability Engineering (SRE) and MLOps applied to systems with direct financial implications.
• Effective cross-functional communicator able to translate complex ML, data, and backend information into business-relevant language and vice versa.
• Possesses humility, strong ownership, and prioritizes clarity to complexity in decision-making.

What HelloFresh Offers

• Opportunity to collaborate globally with hubs in Berlin, Warsaw, NYC, Boulder, and Toronto.
• Work on impactful, diverse technical challenges involving ML, backend, data, and product engineering with clear links to business outcomes.
• Engagement in a genuinely AI-native culture with a mandate to grow this approach further.
• Autonomous leadership over technical and engineering decisions in a product-driven setup with end-to-end project ownership.
• Privileges include discounts on HelloFresh meal kits delivered to your home.
• Participation in the company pension program (not applicable to interns or working students).
• Access to discounted memberships for Urban Sports Club and John Reed, yoga classes, and wellness apps such as Headspace and Spill.
• Flexible working hours, options for working from home or abroad, and a budget for home office setup.
• Childcare assistance (excluded for interns and working students).
• Monthly Deutschlandticket allowance to support eco-friendly commuting.
• Learning and development opportunities with internal training and dedicated L&D budget (not for interns).
• Enjoy a modern and comfortable office environment in Berlin-Kreuzberg, along with social activities like team outings, casual Friday drinks, and company runs.

Additional Notes

We value diverse experience and believe many paths lead to success in this role. Candidates who may not meet every criterion but demonstrate potential and enthusiasm are encouraged to apply.