Staff / Senior Software Engineer - Machine Learning (m/f/d)
Axel Springer National Media & Tech GmbH & Co. KG · Berlin, Germany
- On site
- Full-time
- €100,000 / year
- Berlin, Germany
Job highlights
- Design and operate scalable ML recommender systems.
- Implement AI and LLM capabilities into production.
- Own and optimize production ML systems.
- Collaborate with cross-functional teams.
- Drive personalization impact for millions of readers.
About the role
Staff Senior Software Engineer Machine Learning
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.
How you'll make an impact
- 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
What you'll need
- 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
What we offer
- 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: http://www.axelspringer-neubau.de/
Questions and answers about the application process
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: https://career.axelspringer.com/en/rsde
Contact person for this position (reference number REF2735Z) is Marcel Burmester
Key skills/competency
- Machine Learning Engineering
- Recommender Systems
- Python
- Software Engineering
- System Design
- AI/LLM Integration
- Cloud Environments (AWS)
- Experimentation
- Production ML Systems
- Scalability
Skills & topics
- Machine Learning Engineer
- Software Engineer
- Python
- Recommender Systems
- AI
- LLM
- AWS
- Spark
- Production ML
- System Design
- Germany
- Berlin
- Full-time
- Tech
How to get hired
- Tailor your resume: Highlight your experience with production ML systems, recommender systems, Python, and cloud environments like AWS. Quantify your impact where possible.
- Showcase your expertise: Emphasize your system design skills, CI/CD experience, and any contributions to open-source projects or publications in machine learning.
- Prepare for technical interviews: Be ready to discuss your approach to building and operating scalable ML systems, system design challenges, and ML algorithms, particularly recommender systems.
- Demonstrate ownership: During interviews, provide examples of projects where you took full ownership of ML systems from development to production, including monitoring and optimization.
- Research Axel Springer's values: Understand their focus on AI, innovation in journalism, and their five essentials to align your responses with their culture and mission.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the key responsibilities for a Staff Senior Software Engineer Machine Learning at Axel Springer?
- As a Staff Senior Software Engineer Machine Learning at Axel Springer, you will be responsible for designing, building, and operating scalable recommender systems end-to-end. This includes feature engineering, modeling, production serving, integrating AI/LLM capabilities, writing production-quality code, owning ML systems in production, and collaborating with cross-functional teams. You will also focus on improving engineering standards and system robustness.
- What technical skills are essential for this Staff Senior Software Engineer Machine Learning role?
- Essential technical skills include several years of experience operating ML systems in production at scale, strong software engineering fundamentals (system design, CI/CD, testing), a solid data science foundation in recommender systems, proficiency in Python, and experience with backend languages like Go or Java. Experience with cloud environments (AWS, Spark/PySpark) and integrating modern AI systems like LLMs is also crucial.
- How does Axel Springer leverage AI and Machine Learning in their business?
- Axel Springer places AI at the center of its corporate strategy, believing it will shape the future of media by fusing artificial intelligence with human creativity. The National Media & Tech division acts as a central tech hub, ensuring journalism is supported by state-of-the-art technology. This role specifically focuses on AI-driven approaches for personalization and recommender systems to enhance user experience and business models.
- What is the work arrangement for this Staff Senior Software Engineer Machine Learning position at Axel Springer?
- Axel Springer promotes a collaborative environment with an 80% office presence and 20% mobile working arrangement. The role is a permanent full- or part-time position located in a modern office in the heart of Berlin.
- What opportunities for professional growth are available at Axel Springer for a Staff Senior Software Engineer Machine Learning?
- Axel Springer highly values personal growth, offering extensive opportunities including trainings, learning lunches, tech conferences, and a budget for workshops. They aim to help you expand your knowledge and skills significantly.
- How does Axel Springer ensure diversity and inclusion in its hiring process for Machine Learning roles?
- Diversity is a core part of Axel Springer's corporate culture. They encourage applications from all individuals regardless of gender, nationality, ethnic and social origin, religion, ideology, disability, age, sexual orientation, and identity. Information about support for severely disabled individuals is also available.