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About the Role
As a Staff Machine Learning Engineer, you will shape and advance our Recommendations product by designing, developing, and operating production-grade machine learning systems for personalized customer experiences and business value. You will provide technical leadership, define architecture, and guide the team in making strong engineering and machine learning decisions, translating ambiguous product opportunities into reliable, scalable systems.
Responsibilities
- Collaborate with Data & AI colleagues, product managers, engineers, and business stakeholders.
- Provide technical leadership for the Recommendations product, defining architecture and technical direction for ML systems.
- Design, build, and operate ML systems for recommendation use cases including candidate generation, ranking, personalization, product discovery, and optimization.
- Translate ambiguous business and product requirements into scalable ML solutions, balancing model quality, latency, reliability, scalability, and maintainability.
- Lead technical design and architectural decisions for complex ML initiatives.
- Develop robust ML pipelines for feature engineering, training, evaluation, deployment, monitoring, and continuous model improvement.
- Deploy models into production using a cloud-based stack, ensuring reliability, observability, and maintainability.
- Identify and drive improvements to increase the effectiveness and scalability of the recommendation stack.
- Communicate technical decisions, assumptions, limitations, and uncertainty clearly to stakeholders.
- Raise the technical bar through design reviews, mentoring, knowledge sharing, and establishing ML engineering standards.
Requirements
- Extensive hands-on experience as a Machine Learning Engineer, ML-focused Software Engineer, or Data Scientist with strong engineering experience.
- Proven experience building and operating production-grade machine learning systems, pipelines, or model-based products.
- Demonstrated technical ownership of complex ML systems.
- Strong experience with recommender systems, ranking, personalization, or related product discovery systems.
- Demonstrated technical leadership, influencing architecture, engineering practices, and technical direction.
- Comfort working with complex data and understanding common ML failure modes.
- Ability to reason about system-level trade-offs and make pragmatic technical decisions.
- Ability to explain complex technical topics and trade-offs clearly to technical and non-technical stakeholders.
- Proactive ownership of ambiguous, cross-cutting problems and ability to drive technical initiatives across team boundaries.
- Value collaboration, give and receive feedback openly, and actively help other engineers grow.
Skills
- Machine Learning
- Software Engineering
- Data Science
- Recommender Systems
- Ranking
- Personalization
- Product Discovery
- ML Pipelines
- Cloud Computing
- Technical Leadership
- System Architecture
- Mentoring
- Knowledge Sharing
Location
- EU
Work Type
- Work from Home
- Remote
Experience Level
- Staff
Benefits
- Urban Sports Club membership
- Access to psychologists via Likeminded
- Work from Home flexibility (up to 20 days/year anywhere in the EU)
- Fully costed Deutschland Ticket
- Support for personal development through trainings
About the Company
- Europe’s No.1 e-pharmacy powered by passionate teams and cutting-edge innovation.
- Strives to create a healthy, collaborative work environment where every employee feels valued and inspired.
- Vision: “Until every human has their health”.