Senior Staff Machine Learning Engineer, Menu Personalisation

About the role

You define and own the end-to-end ML systems that power menu personalisation for millions of HelloFresh customers globally. You will set the technical direction for the recommender stack, balancing experimentation velocity with production reliability and scalability. You partner with Data Scientists, Data Engineers, Backend Engineers, and Product to move ideas from initial hypothesis to robust, scalable services. Your decisions will shape the platform for years and directly influence whether customers discover recipes they love each week. You are expected to hold a clear point of view on where personalization should go and to back it with data and user evidence. You will raise the technical bar by mentoring peers, driving architecture reviews, and exemplifying production ML craft across the team.

Key facts

What you'll do

Set the technical direction for the ML systems behind menu personalisation, owning the full lifecycle of feature pipelines, training workflows, model serving, experimentation tooling, and infrastructure.

Take research and experiments to reliable production systems, collaborating with Data Scientists to ensure services meet strict latency, scalability, and observability requirements.

Shape the personalization roadmap with Product and Engineering leadership, grounding your proposals in data and user evidence to drive long-term outcomes.

Operate what you build, prioritising instrumentation, monitoring, and improvements in production because shipping marks the start of the learning cycle, not its end.

Raise the technical bar across the team through rigorous architecture reviews, hands-on mentorship, and clear standards for production ML practice.

Shape long-term architecture and make platform decisions whose benefits unfold over years rather than quarters, ensuring durability and optionality.

Drive engineering excellence beyond Menu Personalisation by defining standards that other ML and data teams adopt across HelloFresh.

Sync with peers across HelloFresh on best practices and contribute to company-wide initiatives that advance ML and data engineering craft at scale.

Requirements

Bring 8+ years of experience building and operating production ML systems, with a track record of technical leadership that scaled.

Show architectural decisions from your past that remained effective over multiple years and influenced teams beyond your own.

Demonstrate strong prior experience with recommender systems or large-scale personalisation in production environments.

Show fluency across the data and ML stack, including Python and Spark, and hands-on experience with backend and platform technologies such as Go, Kafka, and Kubernetes.

Have hands-on experience across feature pipelines, model serving, and observability in high-scale production environments.

Bring statistical literacy to design honest experiments and the judgment to know whether results support your hypotheses.

Show deep understanding of the trade-offs between exploration and exploitation in personalisation systems and how to validate them with data.

Communicate clearly and persuasively, translating technical complexity into decisions and rationale for both technical and non-technical stakeholders.

Practical notes

The role is based in Warszawa, Masovian Voivodeship, Poland, and is a single position within the Menu Personalisation team. HelloFresh is a global food solutions group and the world's leading meal kit company, active in 18 countries across 3 continents, with a mission to change the way people eat forever through high-quality food and recipes. You will work closely with Data Scientists, Backend Engineers, Data Engineers, and ML Engineers to move from experiment to production, focusing on the recommender systems that match customers to recipes. The team believes in owning problems end-to-end, using AI as a force multiplier, and shifting from task execution to trusted problem ownership. Decisions you make will impact platform direction for years, requiring both strategic thinking and hands-on implementation across pipelines, training workflows, model serving, and infrastructure. You will be expected to validate ideas with customers and data, operate services in production, and continuously improve instrumentation and reliability. The role involves setting standards for experimentation, observability, and engineering excellence that can influence company-wide initiatives. Success requires statistical literacy, experience designing experiments, and the ability to judge whether evidence supports your point of view. You will sync with peers across HelloFresh to share best practices and contribute to broader ML and data engineering craft. This is a senior-level position that demands architectural patience, long-term thinking, and the ability to balance innovation with reliability.