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Applied Senior/Staff Scientist for Relational Enterprise Data (T3/T4) (f/m/d)

SAP
Garching bei München, DE, 85748, Germanyfull_timeVerifiedPosted 9 Mar 2026

About the role

We help the world run better
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed. 

 

What you`ll do: 

 

As the Applied Senior/Staff Scientist for Relational Enterprise Data, you will lead the mission to evolve the SAP-RPT model family into experts of structured business data. You will tailor our foundation models to the unique complexities of real-world SAP applications, supercharging them with the deep-seated business process intuition and specialized reasoning required for the enterprise. 

 

Bridging the gap between research scientists focusing on model architecture and data experts, you will ensure our models are not just technically sound, but business-fluent. This is a hands-on role where you will directly implement the techniques that allow our models to navigate the intricacies of relational schemas and enterprise logic. 

 

This is the ideal role for a highly focused, ambitious individual with both a strong technical and coordinating background and your chance to contribute to one of the very few leading foundation models of European origin. 

 

The Role: 

 

  • Tailor the SAP-RPT model family to the unique complexities of real-world relational enterprise data, enabling models to navigate and reason over intricate schemas and logic 

  • Bridge the gap between model architecture research and data experts to ensure models are technically sound and business-fluent 

  • Work hands-on to embed deep-seated business knowledge into foundation models through rigorous experimentation and performance evaluation 

  • Stay at the forefront of Deep Learning, Foundation Models, and Generative AI to drive the strategic evolution of the SAP-RPT family 

  • Contribute to the development of one of the few leading foundation models of European origin, ensuring it meets the specific needs of global enterprise applications 

 

What you bring: 

 

  • PhD or Master's degree in Computer Science, Artificial Intelligence, or other relevant disciplines with 5+ years of professional experience in developing machine learning models. 

  • Extensive hands-on experience with Machine Learning on structured, tabular, or relational enterprise data (e.g., ERP, CRM), with a preference for experience involving SAP S/4HANA schemas and business logic. 

  • Technical mastery of Deep Learning and Transformer architectures, with a proven track record of their application to structured enterprise data and the adaptation of large-scale foundation models to represent complex relational logic and business processes. 

  • Software engineering excellence in Python, with a proven track record of building and scaling experiments using frameworks like PyTorch or TensorFlow. 

  • Strong communication and collaboration skills, with the ability to work effectively in cross-cultural teams. 

 

Meet your team: 

 

SAP is uniquely positioned to lead the next wave of AI by infusing intelligence directly into the business processes that run the world. Our team’s mission is to develop Foundation Models for structured data, starting with the launch and continued evolution of SAP-RPT-1. As the first generation of our relational model portfolio, SAP-RPT-1 represents our commitment to pioneering new research in a domain where SAP’s expertise in enterprise data structures provides an unmatched competitive edge. We are looking for innovators to join us in this journey to develop next-generation models with even higher impact, bridging the gap between cutting-edge AI research and the complex, structured reality of global enterprise data.  

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Company

SAP

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