Staff ML Engineer, Product Recommendations (m/f/d)

About your tasks:

• Work with colleagues from our Data & AI department and collaborate closely with product managers, engineers, and business stakeholders.
• Provide technical leadership for our Recommendations product, helping define the architecture, technical direction, and longer-term evolution of our machine learning systems.
• Design, build, and operate machine learning systems for recommendation use cases such as candidate generation, ranking, personalization, product discovery, and recommendation 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 and help the team navigate trade-offs across modeling, data, infrastructure, and product requirements.
• 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.
• Identify technical risks, gaps, and opportunities across the recommendation stack and drive improvements that increase the effectiveness and scalability of the overall system.
• Communicate technical decisions, assumptions, limitations, and uncertainty clearly to product, engineering, and business stakeholders.
• Raise the technical bar through design reviews, mentoring, knowledge sharing, and by establishing ML engineering standards and best practices within and beyond the team.

Qualifications

About you:

• You have extensive 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 and have taken technical ownership of complex ML systems.
• You have strong experience working with recommender systems, ranking, personalization, or related product discovery systems.
• You have demonstrated technical leadership, influencing architecture, engineering practices, and technical direction beyond your own individual contributions.
• 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 can reason about system-level trade-offs and make pragmatic technical decisions across model quality, latency, reliability, scalability, and maintainability.
• You enjoy working close to the business and can explain complex technical topics and trade-offs clearly to technical and non-technical stakeholders.
• You take ownership of ambiguous, cross-cutting problems, work proactively, and can drive technical initiatives across team boundaries.
• You value collaboration, give and receive feedback openly, and actively help other engineers grow through mentoring and technical guidance.

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 :)