opengreenhouseremotely
Senior Machine Learning Engineer, Menu Personalization
HelloFresh AG
LocationWarszawa, Masovian Voivodeship, Poland
Last observed2026-06-13 05:25:43.896552
Job idremotely-hellofresh:greenhouse:7963148
Work with HelloFresh in Warsaw and its HelloTech organisation, HelloFresh’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month. Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech. HelloTech works in autonomous, cross-functional alliances, each owning a specific product or domain end to end. By working with our Warsaw office, you will help shape scalable, data-driven products used across our markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy HelloFresh’s products, today and in the future. About the Team Menu Personalization determines what millions of customers see when they open HelloFresh each week. The team handles the recommender systems that match customers to recipes across global markets, bringing together Data Scientists, Backend Engineers, Data Engineers, ML Engineers, and Product to take ideas from experiment to production. The work directly shapes customer experience and business growth: when personalization improves, customers find recipes they love faster, and HelloFresh becomes a stronger weekly habit. At HelloTech, the model moves away from software developers executing tickets toward one where engineers are trusted to resolve customer problems. This involves taking a problem statement, forming a point of view, validating it with data, and shipping solutions using AI as a force multiplier. About the role: What's in the Box This position is for a Senior Machine Learning (ML) Engineer for the Menu Personalization team to help build and operate the recommender stack running in production. The service provider will design, build, and operate ML systems across feature pipelines, training workflows, model serving, experimentation tooling, and the underlying infrastructure, holding end-to-end accountability for significant parts of the stack. The role involves bringing a distinct point of view on how to improve personalization, backed by data and user evidence. The provider will partner with Data Scientists to transition models from notebooks to production, with Data Engineers on features and pipelines, with Backend Engineers on online inference paths, and with Product on future roadmaps. This role does not include people management responsibilities. At HelloTech, flexibility and cross-functional collaboration are core to how we work. While this role is aligned to a specific Alliance, strong candidates may also be considered for opportunities across different teams or projects. What you’ll do: The Recipe Build and operate the ML systems behind menu personalization, working hands-on across feature pipelines, training workflows, model serving, experimentation tooling, and infrastructure. Transition research and experiments into reliable production systems, partnering with Data Scientists on services that meet real latency, scalability, and observability requirements. Maintain accountability for significant components of the recommender stack, from design through deployment and ongoing operation. Operate deliverables , instrumenting and improving systems in production to ensure continuous refinement based on real-world performance. Contribute to the personalization roadmap with Product and Engineering, backing technical directions with data and user evidence. Raise the technical bar on the team through thorough code and design rev
This page is generated from the committed OpenOpps static snapshot. Use the source posting or apply link for the employer's current canonical posting state.