Senior Machine Learning Product Engineer, Menu Personalization, Consumer Alliance (all genders)

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 its 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.

HelloFresh’s 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 its 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 the Warsaw office, you will help shape scalable, data-driven products used across markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy HelloFresh’s products.

Quick Facts

• Work with HelloTech’s international teams in Warsaw.
• Build and operate modern systems at global scale, supporting 6+ million customers and complex supply-chain operations.
• This role has no people-management responsibilities.

About the Team

Menu Personalization determines what millions of customers see when they open HelloFresh each week. As a Senior Machine Learning Product Engineer, you will shape how millions of customers discover and curate their weekly meals across global digital platforms.

You will handle 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.

Description

This position is for a Senior Machine Learning Product Engineer for the Menu Personalization team to help build and operate the recommender stack running in production. You will design, build, and operate ML systems across feature pipelines, training workflows, model serving, experimentation tooling, and underlying infrastructure, holding end-to-end accountability for significant parts of the stack.

You will bring 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.

At HelloTech, flexibility and cross-functional collaboration are core to how work is done. While this role is aligned to a specific Alliance, strong candidates may also be considered for opportunities across different teams or projects.

Responsibilities

• 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.
• Instrument and improve 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 through thorough code and design reviews, technical guidance, and an example of production ML craft.
• Work beyond your specialization when the problem demands it.
• Operate what you build: instrument, monitor, and improve systems in production. Shipping is the beginning of the learning cycle, not the end.

Requirements

• Hands-on experience working with AI tooling, such as Claude Code, Cursor, and Copilot, beyond casual experimentation.
• Daily use of AI agents, with practical judgment about how context shapes output quality and how to set boundaries on AI-generated work.
• Ideally, 5 years of experience building and operating production ML systems.
• Fluency across the data and ML stack, including Python and Apache Spark.
• Working knowledge of Kafka and Kubernetes.
• 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 statistical literacy to design sound experiments and interpret results.
• Operational judgment to diagnose system misbehavior under real load, identify root causes, and deploy robust fixes.
• Full ownership, a bias to ship, product sense, and the ability to support technical opinions with data and user evidence.

Production experience with recommender systems or large-scale personalization is a strong plus.

Benefits

• Global collaboration at scale with experienced engineers and product partners across international teams, in a culture of active knowledge sharing.
• Technology with real-world impact, supporting 6+ million customers and complex supply-chain operations.
• Technical, product, and design leadership: drive best practices and influence architecture, design, quality, and ways of working in an autonomous, product-led setup.
• End-to-end development and delivery: drive decisions from problem definition to production, improving systems and enabling long-term scalability.
• Access to workspace in central Warsaw at Prosta 20, with modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments such as coffee, soft drinks, and fruit.