Senior ML Manager (m/f/d) at Redcare Pharmacy

Cologne, North Rhine-Westphalia, Germany -

Full Time

Start Date

Immediate

Expiry Date

21 May, 26

Salary

0.0

Posted On

20 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

ML System Development, ML System Operation, Team Leadership, ML Engineering, Quality Standards Enforcement, Cross-functional Collaboration, AI, Data Science, Product Management, Technical Expertise, Architecture Decisions, Stakeholder Communication, CI/CD Pipelines, Containerization, ML Ops, Recommender Engines

Industry

Retail Pharmacies

Description

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 start your #Redcareer today. About the role: This is a unique opportunity to shape the future of Redcare’s data and AI landscape. As a strategic investment at the core of our company, you will be instrumental in building and scaling a team where your decisions will make a direct business impact. About the tech stack: We work with modern machine learning technologies and platforms, cloud-based infrastructure, CI/CD pipelines, containerization, and ML Ops tools. We are also open to introduce new technology when it enables our teams and business. Job Description About your tasks: Drive the development and operation of production-grade ML systems that power revenue-generating services like recommender engines and search. Lead and grow a team of currently 5 ML engineers (with future expansion), fostering their development and performance. Define and enforce quality standards across the ML engineering discipline, setting the benchmark for excellence. Collaborate closely with cross-functional teams including AI and Data Science, product management, and stakeholders to align on goals and drive innovation. Remain hands-on, bringing deep technical expertise to guide architecture decisions and ensure robust implementations. Qualifications About you: Proven leadership experience, ideally in managing high-performing ML engineering teams. Strong background in building and running ML systems in production, especially those with direct business impact. Comfortable with internal stakeholder communication and cross-functional alignment. You thrive in dynamic environments and care deeply about building things the right way. You understand how to ensure quick iteration cycles in order to achieve business impact fast while enforcing rigorous technical quality standards in our products. Additional Information About your benefits: In order to provide you with the best possible support for your individual needs - whether it‘s living a healthy life, having enough time for your family, or developing your skills - we offer a wide range of different, site-specific benefits: Welcome days: We want you to feel at home with us from the very first day. Therefore, we welcome you with our comprehensive onboarding program. 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. 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. Personal development: Grow! We support and encourage your individual development through various in- and external trainings. Kindergarten Grant: We offer our employees who pay for childcare in kindergarten 100,00 € (total) per month. Mental health: Get quick professional help from psychologists from nilo if you feel overwhelmed in your personal or professional life. Anonymously and free of charge. Remote Type: Tech, Product, IT & Data

Responsibilities

The role involves driving the development and operation of production-grade ML systems, such as recommender engines and search, that generate revenue. A key responsibility is leading and growing a team of ML engineers while defining and enforcing high-quality standards across the ML engineering discipline.