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4 дня назад

Senior ML Engineer, Retail Media

Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
Germany
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Senior ML Engineer, Retail Media (Machine Learning/Retail Media): Building production-grade machine learning systems for sponsored product ranking, audience segmentation, campaign optimization, attribution, and performance measurement with an accent on scalable pipelines, model quality, latency, and reliability. Focus on deploying, monitoring, and continuously improving ML models while solving data leakage, feedback loops, distribution shifts, and misleading offline metrics.

Location: Cologne, Germany. Individual work-from-home arrangements may be available, including up to 20 days per year anywhere in the EU.

Company

hirify.global is a leading European e-pharmacy developing digital health and retail solutions.

What you will do

  • Design, build, and operate machine learning systems for retail media use cases, including sponsored product ranking, audience segmentation, campaign optimization, attribution, and performance measurement.
  • Translate product and business requirements into scalable ML solutions while balancing model quality, latency, reliability, scalability, and maintainability.
  • Develop pipelines for feature engineering, training, evaluation, deployment, monitoring, and continuous model improvement.
  • Bring models into production using a cloud-based stack and ensure they remain reliable, observable, and maintainable.
  • Collaborate with Data & AI colleagues, product managers, engineers, and commercial stakeholders.
  • Communicate technical decisions, assumptions, limitations, and uncertainty, and contribute to ML engineering standards and knowledge sharing.

Requirements

  • Several years of hands-on experience as a Machine Learning Engineer, ML-focused Software Engineer, or Data Scientist with strong engineering experience.
  • Experience building and operating production-grade machine learning systems, pipelines, or model-based products.
  • Experience with retail media, recommender systems, or ranking.
  • Understanding of complex data and ML failure modes, including data leakage, feedback loops, distribution shifts, and misleading offline metrics.
  • Ability to explain complex technical topics clearly to non-technical stakeholders and work effectively in an ambiguous early-stage product environment.
  • Strong ownership, proactive collaboration, openness to feedback, and interest in helping others grow.

Culture & Benefits

  • Collaborative work with Data & AI, product, engineering, and business teams.
  • Individual work-from-home arrangements where the role allows it, including up to 20 days per year anywhere in the EU.
  • Urban Sports Club membership package.
  • Anonymous, free professional mental health support through Likeminded.
  • Fully funded Deutschland Ticket.
  • Support for individual development through internal and external training.

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