Axel Springer
Tech / AI / Software
Staff/SeniorSoftwareEngineer-MachineLearning(m/f/d)
Neural analysis suggests this role is
optimal for mid candidates.
“Staff / Senior Software Engineer - Machine Learning (m/f/d) at Axel Springer. Skills: ML engineering expertise, data science foundation in recommender systems, personalization at scale, scalable recommender systems end-to-end, AI and LLM-based capabilities into scalable production systems, ML systems in production. 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 capa”
What You'll Achieve.
delivering measurable impact for millions of readers; strengthen and expand the role of artificial intelligence in our products and journalism; continuously improve recommender performance and system design; Continuously improve engineering standards, tooling, experimentation practices, and system robustness
Industry & Context.
solution-oriented mindset
What They're Looking For.
Must Have
Several years of hands-on experience operating machine learning systems in production at scale, 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, working knowledge of backend languages such as Go or Java, 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), background in experimentation and controlled rollouts in production environments, A pragmatic, solution-oriented mindset with a builder mentality and ownership attitude, Ability to operate confidently as a senior engineer within cross-functional product and engineering teams
Nice to Have
German skills are an advantage
What You'll Do.
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
and testable production-quality code with a focus on reliability and long-term maintainability
Take full ownership of ML systems in production
performance optimisation
and system resilience
Enable controlled experimentation and continuous optimisation of recommender systems in production environments
Proactively experiment with new approaches
and architectures to continuously improve recommender performance and system design
How You'll Work.
Team & Collaboration
Collaborate closely with data scientists, software engineers, data engineers, and product managers to integrate ML solutions into scalable, production-ready system architectures
Communication Scope
Excellent communication skills
Full Job Description
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. * 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 deplo
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