Staff Machine Learning Engineer - Product Recommendations

About Redcare Pharmacy

Redcare Pharmacy is recognized as Europe’s leading e-pharmacy, driven by dedicated teams and state-of-the-art innovation. We foster a healthy and collaborative work atmosphere where every employee feels appreciated and motivated to contribute to our vision "Until every human has their health." Join us for a meaningful career that aligns with your values and start your journey with Redcare Pharmacy.

Role Overview

As a Staff Machine Learning Engineer in our Recommendations product team, you will be crucial in designing, developing, and maintaining scalable production-grade ML systems that deliver personalized product experiences to customers and drive measurable business value.

You will collaborate extensively with colleagues in Data & AI, product managers, engineers, and business stakeholders throughout the ML lifecycle – from defining problems and exploring data to model creation, deployment, ongoing monitoring, and iterative enhancement.

In addition to hands-on development, this leadership role involves guiding the technical vision and architecture for recommendation systems, supporting engineering excellence, and helping peers navigate engineering and ML decisions.

Key Responsibilities

• Collaborate with the Data & AI team and work closely with product, engineering, and business stakeholders.
• Provide technical guidance and leadership for the Recommendations product’s architecture and strategic direction.
• Design, implement, and manage ML systems supporting use cases such as candidate generation, ranking, personalization, product discovery, and optimization of recommendations.
• Convert ambiguous business needs into scalable ML solutions, balancing model accuracy, response latency, system reliability, scalability, and ease of maintenance.
• Lead architectural decisions and technical design for complex ML projects, helping evaluate trade-offs across modeling, data handling, infrastructure, and product requirements.
• Develop reliable ML pipelines encompassing feature engineering, training, evaluation, deployment, monitoring, and continuous improvement.
• Deploy models within our cloud-based infrastructure ensuring production robustness, observability, and maintainability.
• Identify and address technical risks and gaps in the recommendation systems, driving improvements to boost system efficiency and scalability.
• Communicate clearly the technical rationale, assumptions, constraints, and uncertainties to both technical and non-technical stakeholders.
• Raise the team’s technical standard through design reviews, mentoring, knowledge sharing, and by defining ML engineering best practices.

Candidate Profile

• Proven experience as a Machine Learning Engineer, ML-focused Software Engineer, or Data Scientist with strong software engineering skills.
• Experience in building and managing production-grade machine learning systems or model-centric products with technical ownership of complex ML environments.
• Strong background with recommender systems, ranking algorithms, personalization, or other related product discovery technologies.
• Demonstrated ability to provide technical leadership, influence system architecture, engineering methodologies, and strategic direction beyond individual contributions.
• Comfortable handling complex datasets and aware of common ML pitfalls such as data leakage, feedback loops, distribution shifts, and unreliable offline metrics.
• Ability to make pragmatic trade-offs involving model quality, latency, reliability, scalability, and maintainability at the system level.
• Effective communicator who can explain technical details and trade-offs clearly to stakeholders from diverse backgrounds.
• Proactive in managing ambiguous, cross-functional challenges and capable of leading technical initiatives across team boundaries.
• Collaborative mindset with a willingness to openly share feedback, mentor others, and foster professional growth within the team.

Additional Information - Employee Benefits

• Health & Fitness: Access to an Urban Sports Club membership providing a wide selection of sporting activities.
• Mental Health Support: Free and anonymous consultations available with licensed psychologists via Likeminded to support personal and professional challenges.
• Flexible Remote Work: If the role allows, arrangements for working from home at customized locations including up to 20 days per year anywhere within the EU.
• Mobility: Provision of a fully covered Deutschland Ticket for unlimited public transport use.
• Personal Development: Encouragement and financial support for individual growth through varied internal and external training opportunities.
• Additional perks and benefits to enhance work-life balance and employee satisfaction.