WE HELP THE WORLD RUN BETTER

At SAP, we enable you to bring out your best. Our company culture is focused on collaboration and a shared passion to help the world run better. How? We focus every day on building the foundation for tomorrow and creating a workplace that embraces differences, values flexibility, and is aligned to our purpose-driven and future-focused work. We offer a highly collaborative, caring team environment with a strong focus on learning and development, recognition for your individual contributions, and a variety of benefit options for you to choose from.

At SAP, we are bringing together state-of-the-art AI technology with our extensive industry-specific data and deep process knowledge to create innovative AI capabilities across SAP products & services. Large Language Models (LLMs) hold immense potential to change the way we work and develop products. They are reshaping the landscape of Machine Learning across various domains. However, their limited ability to leverage structured / tabular data leaves a considerable share of enterprise data untapped. It is SAP’s mission to overcome this challenge within the realm of Business AI. Our goal is to adapt Foundation Models with SAP data, enabling our customers to run their business processes more efficiently. Strong research collaborations with academic and commercial partners are instrumental to achieve that goal. The Role:

• Establish, scope and guide SAP-funded research projects at renowned international universities as well as commercial partners.
• Contribute pioneering technical advances to the development of our Foundation Models, with a strong emphasis on hands-on coding, experimentation, and model improvement.
• Stimulate academic research by publishing Business AI–relevant problem statements, frameworks, and data sets, and by translating project innovations into impactful research publications and thought leadership in Foundation Models and Generative AI.
• Keep the pulse with the research, providing insights into the latest research findings and making them comparable with internal work