Job Description
About your tasks:
- Work with colleagues from our Data & AI department and collaborate closely with product managers, engineers, and commercial stakeholders.
- Design, build, and operate machine learning systems for retail media use cases such as sponsored product ranking, audience segmentation, campaign optimization, attribution, and performance measurement.
- Translate business and product requirements into scalable ML solutions, balancing model quality, latency, reliability, scalability, and maintainability.
- Develop robust ML pipelines for feature engineering, training, evaluation, deployment, monitoring, and continuous model improvement.
- Bring models into production using our cloud-based stack and ensure they are reliable, observable, and maintainable over time.
- Communicate technical decisions, assumptions, limitations, and uncertainty clearly to product, engineering, and business stakeholders.
- Contribute to ML engineering standards, best practices, and knowledge sharing within the team.
Qualifications
About you:
- You have several years of hands-on experience as a Machine Learning Engineer, ML-focused Software Engineer, or Data Scientist with strong engineering experience.
- You have built and operated production-grade machine learning systems, pipelines, or model-based products.
- You have experience working with retail media, or alternatively recommender systems or ranking.
- You are comfortable working with complex data and understand common ML failure modes such as data leakage, feedback loops, distribution shifts, and misleading offline metrics.
- You enjoy working close to the business and can explain complex technical topics clearly to non-technical stakeholders.
- You take ownership, work proactively, and are comfortable navigating ambiguity in an early-stage product environment.
- You value collaboration, give and receive feedback openly, and enjoy helping others grow.
Additional Information
About your benefits:
In order to provide our employees with the best possible support for their individual needs, we offer a wide range of benefits:
- Sports: Stay healthy. Profit from a membership (M) package at Urban Sports Club, so that you can take advantage of a huge variety of sport offers.
- Mental Health: Get quick and professional help from psychologists of Likeminded if you feel overwhelmed in private or professional life. Anonymous and free of charge.
- Work from Home: If your job does not require you to be present in the office, we can arrange the place you work from individually - even for up to 20 days a year anywhere in the EU.
- Mobility: We provide our employees with a fully costed Deutschland Ticket which can be used at any time. Click here to learn more.
- Personal development: Grow! We support and encourage your individual development through various in- and external trainings.
- And many more :)
Company Description
About Redcare Pharmacy:
As Europe’s No.1 e-pharmacy, Redcare Pharmacy is powered by passionate teams and cutting-edge innovation. We strive to create a healthy, collaborative work environment where every employee feels valued and inspired to contribute to our vision “Until every human has their health”. If you’re seeking a career that offers purpose and aligns with your values, join us and begin your #Redcareer today.
About the role:
As a Senior Machine Learning Engineer, you will help build our new Retail Media product from the ground up. You will design, develop, and operate production-grade machine learning systems that create relevant advertising experiences for customers and measurable value for brands and retailers.
You will work in a high-impact product team, working with Data & AI colleagues as well as collaborating closely with product, engineering, and business stakeholders. Your work will cover the full ML lifecycle - from problem framing and data understanding to model development, deployment, monitoring, and continuous improvement.
This role is suited for someone who combines strong machine learning expertise with solid software engineering practices and enjoys turning ambiguous product opportunities into reliable, scalable systems.