$ cat jobs/senior-director-of-machine-learning-engineering-hellofresh-3bf4f92a27fd.json
Senior Director of Machine Learning Engineering
The CVO Tribe CVO owns two of HelloFresh's largest economic levers: benefit optimization and pricing . The tribe uses machine learning, personalization, and lifetime-value prediction to replace manual, rules-based decisioning with data-driven systems. The engineering org is globally distributed across Berlin, Warsaw, NYC, Boulder, and Toronto, and includes Frontend, Backend, Data, and ML Engineering, working closely with embedded Data Scientists. The work spans a genuinely mixed engineering profile: ML-heavy systems for benefit recommendation, personalization, and customer lifetime-value forecasting, alongside backend and distributed-systems work powering pricing infrastructure and subscription products at scale. As Senior Director, based in Berlin, you'll lead this full spectrum, setting technical strategy across ML, backend, and data disciplines and across time zones, without relying on daily co-location. What you'll do Lead an organization of 25-30 engineers, data scientists, and ML practitioners across Berlin, Warsaw, NYC, Boulder, and Toronto, through a layer of Engineering Managers and Staff Engineers reporting into you. Own ML strategy for benefit recommendation, personalization, and customer lifetime-value forecasting, as well as backend and distributed-systems strategy for pricing and subscription infrastructure. Drive the transformation of ways of working toward fully GenAI-native, cross-functional product teams, building on teams that already ship the majority of their code with AI assistance. Own reliability and operational excellence across both ML and backend systems: observability from model output through to customer-facing delivery, SLOs/SLIs, incident management, and MLOps practices such as retraining, rollback, and experiment tracking. Partner with Product, Data Science, Marketing, Finance, and adjacent engineering teams to align engineering priorities with business outcomes. Manage and develop Engineering Managers and Data Science Leads across di
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