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

HelloFresh
Warsaw
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningSkills: ["Product sense","Ownership","Bias to ship","Data-driven decision-making","Cross-functional collaboration"]

Build and operate the production recommender systems behind HelloFresh’s Menu Personalization, taking end-to-end accountability across feature pipelines, training workflows, model serving, experimentation tooling, and infrastructure. Partner closely with data scientists, data engineers, backend engineers, and product to transition models from notebooks to reliable, low-latency services. Instrument and improve the stack in production to refine personalization with data and real-world user evidence.

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FursaFursa
HelloFresh
HelloFresh
3 days ago

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

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Source: Company careers pageValidated by: Fursa AI
Last checked: 11 hours agoStatus: Live

Job Summary

Build and operate the production recommender systems behind HelloFresh’s Menu Personalization, taking end-to-end accountability across feature pipelines, training workflows, model serving, experimentation tooling, and infrastructure. Partner closely with data scientists, data engineers, backend engineers, and product to transition models from notebooks to reliable, low-latency services. Instrument and improve the stack in production to refine personalization with data and real-world user evidence.
Location: Warsaw
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design, build, and operate ML systems for menu personalization, owning parts of the recommender stack from pipeline to deployment and ongoing operation.
  • •Build data products and ML systems behind menu personalization across feature pipelines, training workflows, model serving, experimentation tooling, and infrastructure.
  • •Transition models and experiments into reliable production systems with data scientists, meeting latency, scalability, and observability requirements.
  • •Maintain accountability for significant components of the recommender stack, instrumenting, monitoring, and improving production performance.
  • •Contribute to the personalization roadmap with product and engineering, supporting technical directions with data and user evidence.

Key Requirements

  • •5 years (ideally) of experience building and operating production ML systems.
  • •Fluency across the data/ML stack (Python, Apache Spark) and working knowledge of backend/platform stack (Kafka, Kubernetes), including 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 experiments and interpret 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.
Skills:Product senseOwnershipBias to shipData-driven decision-makingCross-functional collaboration
Languages:English
Tech Stack:Claude CodeCursorCopilotPythonApache SparkKafkaKubernetes

Company Brief

HelloFresh
HelloFresh is a meal-kit and food subscription company that delivers fresh ingredients and recipes to consumers, offering convenient home-cooked meals through weekly subscription boxes across multiple international markets.
Industry: FoodTech
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Berlin, Germany
Founded: 2011
Glassdoor
Glassdoor: 3.6
WebsiteLinkedIn