Axel Springer is Europe’s leading digital publisher and a global media and technology company headquartered in Berlin. With renowned brands such as BILD, POLITICO Germany, WELT und BUSINESS INSIDER Germany, we reach millions of users worldwide. We combine the reach of an established industry leader with the agility of a startup, constantly driving innovation to transform journalism for the digital age.
Our corporate strategy places AI at the center: “Digital is the new print. AI is the new digital.” This vision reflects our belief that the fusion of artificial intelligence and human creativity will shape the future of media. Our National Media & Tech division is the central tech hub that ensures our journalism is supported by state-of-the-art technology, positioning our brands to thrive in the digital age. We believe in the future of journalism as a business model and invest in forward-looking technologies. Our five essentials are the values that unite us and guide us in our commitment to freedom.
This role combines deep ML engineering expertise with a solid data science foundation in recommender systems. You will own and evolve the systems that drive personalization at scale, delivering measurable impact for millions of readers.
In this role, you will design and operate scalable, production-grade ML systems while continuously exploring new AI-driven approaches to strengthen and expand the role of artificial intelligence in our products and journalism.
We are looking for a curious builder who takes ownership and continuously seeks better solutions.
Job Description
* Architect and build scalable recommender systems end-to-end, from feature engineering and modeling to reliable production serving
* Implement and integrate modern AI and LLM-based capabilities into scalable production systems
* Write clean, maintainable, and testable production-quality code with a strong focus on reliability and long-term maintainability
* Take full ownership of ML systems in production, including deployment, monitoring, performance optimisation, and system resilience
* Enable controlled experimentation and continuous optimisation of recommender systems in production environments
* Proactively experiment with new approaches, tools, and architectures to continuously improve recommender performance and system design
* Collaborate closely with data scientists, software engineers, data engineers, and product managers to integrate ML solutions into scalable, production-ready system architectures
* Continuously improve engineering standards, tooling, experimentation practices, and system robustness
Qualifications
* Several years of hands-on experience operating machine learning systems in production at scale
* Strong software engineering fundamentals, including system design, clean architecture, testing strategies, CI/CD, and code reviews
* Solid data science foundation in recommender systems
* Proficiency in Python and working knowledge of backend languages such as Go or Java, with experience building and operating ML systems in distributed, cloud-based environments (e.g., Spark/PySpark, AWS)
* Practical experience integrating modern AI systems such as LLMs into real-world applications
* Experience designing observable, resilient, and scalable ML systems (monitoring, logging, alerting, performance tracking)
* Strong background in experimentation and controlled rollouts in production environments
* A pragmatic, solution-oriented mindset with a strong builder mentality and ownership attitude
* Ability to operate confidently as a senior engineer within cross-functional product and engineering teams
* Excellent communication skills in English; German skills are an advantage
Additional Information
* your personal growth is important to us: we offer trainings and learning lunches, tech conferences, a budget for workshops and much more to expand your knowledge and your skills
* flexible working hours support a healthy work-life balance
* our free food offer: in addition to a breakfast snack, we also offer a free lunch in our canteens
* 30 days vacation plus 10 days working from abroad
* free choice of top-notch office equipment (also for your remote work space and private usage), up-to-date hardware, software and modern office spaces that provide you with maximum flexibility
* collaboration thrives on direct exchange - we rely on 80% office presence and 20% mobile working
* from now a permanent full- or part-time position in a modern office in the heart of Berlin:
The most frequently asked questions and their answers can be found on our FAQ page: career.axelspringer.com/en/faq
Diversity is an essential part of our corporate culture! We are looking forward to receiving all applications regardless of gender, nationality, ethnic and social origin, religion, ideology, disability, age, sexual orientation and identity.
You can find information about the representation for the severely disabled at Axel Springer here: