Senior ML Engineer (Retail Media)

TL;DR

Senior ML Engineer (Retail Media): Designing, developing, and operating production-grade machine learning systems for a new retail media product with an accent on sponsored product ranking, audience segmentation, and campaign optimization. Focus on building scalable ML pipelines, integrating models into a cloud-based stack, and translating business requirements into reliable production systems.

Location: Cologne, Germany (Remote possible)

Company

Europe’s No.1 e-pharmacy focused on providing health accessibility through cutting-edge innovation.

What you will do

• Design, build, and operate ML systems for retail media use cases including sponsored ranking and audience segmentation.
• Translate business and product requirements into scalable, maintainable ML solutions.
• Develop robust pipelines for feature engineering, training, evaluation, and monitoring.
• Deploy models using a cloud-based stack and ensure long-term observability.
• Communicate technical decisions and limitations to product, engineering, and business stakeholders.
• Establish ML engineering standards and best practices within the team.

Requirements

• Several years of experience as an ML Engineer, ML-focused Software Engineer, or Data Scientist.
• Proven track record of building and operating production-grade ML systems and pipelines.
• Experience with retail media, recommender systems, or ranking.
• Deep understanding of ML failure modes such as data leakage, feedback loops, and distribution shifts.
• Ability to explain complex technical topics to non-technical stakeholders.
• Proactive ownership and comfort with ambiguity in early-stage product environments.

Culture & Benefits

• Membership at Urban Sports Club for various sports activities.
• Free anonymous professional psychological support via Likeminded.
• Flexible work-from-home arrangements, including up to 20 days per year from anywhere in the EU.
• Fully funded Deutschland Ticket for mobility.
• Support for individual growth through internal and external trainings.