Job Description

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. As a Senior Machine Learning Product Engineer in this team you will shape how millions of customers discover and curate their weekly meals across our global digital platforms. You will handle 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.

About the role: What's in the Box

This position is for a Senior Machine Learning (ML) Product Engineer for the Menu Personalization team to help build and operate the recommender stack running in production. In this role you 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. You 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

At HelloFresh we are moving away from a model where software developers just execute tickets toward one where product engineers are trusted to own customer problems. A Product Engineer takes a problem, forms a point of view, validates it with customers and data, and ships it using AI as a force multiplier.

• Build and operate data products and 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 reviews, technical guidance, and setting an example for production ML craft.
• Work beyond your specialization when the problem demands it. Your specialization is your anchor, not your boundary.
• Operate what you build. You instrument, monitor, and improve your systems in production. Shipping is the beginning of the learning cycle, not the end.

What you’ll bring: The Ingredients

• Hands-on experience working with AI tooling (e.g., Claude Code, Cursor, Copilot) beyond casual experimentation. You use AI agents every day. You have a practical sense of how the context you provide to AI tools shapes output quality, and how to set boundaries on AI-generated work.
• 5 years (ideally) of experience building and operating production ML systems.
• Fluency across the data and ML stack (Python, Apache Spark) and working knowledge of the backend and platform stack ( Kafka, Kubernetes), with hands-on experience across pipelines, model serving, and observability at scale.
• Deep data/ML engineering expertise, experience operating models or data products in production, and the statistical literacy to design sound experiments and interpret their results.
• Production experience with recommender systems or large-scale personalization is a strong plus.
• Operational judgment to diagnose system misbehavior under real load, identify root causes, and deploy robust fixes.
• You take full ownership. You have a bias to ship. You finish the last twenty percent.
• You have product sense and are opinionated about what should be built and why, and you can back that opinion with data and user evidence.

Above all, we are looking for individuals who will make HelloFresh better. We believe there are many different ways of developing skills and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.

What we offer: The Toppings

• Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech’s international teams, in a culture of active knowledge sharing.
• Technology with real-world impact: Build and operate modern systems at global scale, supporting 6+ millions of customers and complex supply chain operations.
• Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.
• End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.
• Access to workspace at Warsaw centre (Prosta 20). The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit).

Are you the missing ingredient? If this sounds like a tasty opportunity, we’d be excited to hear from you. We aim to review your profile and respond within 5 business days.

#ENGINEERING