About the Role
At SAP’s Business AI Research, we are exploring the next frontier of AI methods on structured business data – graphs, tables, time series, and more. Foundation Models on Structured Data, like SAP-RPT-1, have ushered in the GenAI era for business relevant scenarios – scenarios that have so far been addressed with classical, often tree-based methods. Now, we are taking the next step. We collaborate with our existing applied research teams in creating novel benchmarks for business problems and the development of novel architectures and models, with the goal to publish benchmarks and models at scientific conferences and in the open-source community. We are working jointly with our academic partners to create ever better means of solving real business problems.
Responsibilities
- Drive pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
- Expand the horizon of what is possible by bringing together rich semantic context with large scale business data.
- Define the research agenda for a small squad of research scientists and engineers.
- Enable academic research by providing Business AI relevant problem statements, frameworks and data sets.
- Keep the pulse with novel research, providing insights into the latest research findings and making them comparable with internal work.
- Translate applied research breakthroughs into research publications at relevant top-tier conferences and contribute to thought leadership in foundation and world models on structured data.
- Collaborate closely with various domain specialists and data owners to understand how the data can be used for world model training.
- Contribute to thought leadership in an entirely new field of Foundation and World Models on Structured Data.
- Work closely with the team developing the relational pre-trained transformer (SAP-RPT-1) to exchange information and ensure that internal initiatives and project deliverables are aligned with community best practices.
- Collaborate with established academic partners and define new collaborations with top tier academic researchers.
- Supervise PhD students during summer internships or as part of academic collaborations.
Requirements
- PhD in Computer Science, Artificial Intelligence, physics, mathematics or other relevant disciplines.
- Candidate must have an academic background in one of the following fields: Foundation Models / Machine Learning on large scale structured data, World Models. This should be supported by a substantial record of related publications, including recent works, at top tier conferences and a well-established network in these fields.
- A strong research vision for foundation models on structured data, and of how world models impact the development of such foundation models.
- Extensive research experience with machine learning on structured data.
- Ideally, experience in Causal AI and how it relates to foundation models on structured data.
- Proven experience and deep understanding of the opportunities and challenges associated with collaboration between industrial and academic research.
- Proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or similar. Optionally, hands-on experience with (knowledge) graph technologies.
- Ideally, professional experience with the combination of knowledge graphs and large language models in ERP domain.
- Proven history of leading projects with a strategic mindset complemented by superior organizational abilities.
Meet your team
SAP's AI organization is dedicated to seamlessly infusing AI into all enterprise applications, enabling customers, partners, and developers to enhance business processes and generate remarkable business value. Join our international AI team where innovation thrives, opportunities for personal development abound, and exceptional colleagues collaborate globally.