Limited employment up to 6 months (f/m/d) - Neuro-Symbolic AI: The Next Frontier (6 Months)

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 build

As a Research Fellow in the Global Content Group (GCG) Engineering team, you will:

• Research and prototype neuro-symbolic AI approaches that combine the reasoning power of structured knowledge graphs with the generalization capabilities of large language and foundation models
• Develop methods to inject ontology-level knowledge — concepts, relationships, and constraints — directly into foundation models, enabling them to generate accurate, schema-aware SPARQL queries from natural language
• Design and evaluate knowledge-grounded question answering (Q&A) systems that go beyond retrieval-augmented generation, leveraging formal ontologies to improve precision, explainability, and faithfulness of model outputs
• Benchmark your approaches against existing text-to-SPARQL and semantic Q&A baselines on enterprise knowledge graphs
• Collaborate with a global team of software engineers, data scientists, and researchers on cutting-edge challenges at the intersection of symbolic AI and modern deep learning
• Document and present your research findings, contributing to publications and internal knowledge-sharing

What you bring

• PhD candidate (mid-to-late stage) or postdoctoral researcher in Computer Science, Artificial Intelligence, Natural Language Processing, or a related field
• Strong background in neuro-symbolic AI, knowledge representation, or semantic web technologies (RDF, OWL, SPARQL)
• Hands-on experience with large language models or foundation models — fine-tuning, prompt engineering, or knowledge injection techniques
• Familiarity with text-to-SPARQL, semantic parsing, or knowledge graph question answering (KGQA)
• Solid programming skills in Python; experience with ML frameworks (PyTorch, Hugging Face) and knowledge graph tooling is a plus
• Research track record in neuro-symbolic systems, NLP, or knowledge graphs — with publications
• Ability to drive independent research and translate findings into working prototypes
• Good communication skills in English (written and spoken); German is a plus
• Available for a 6-month research fellowship (full-time or part-time)

Where you belong

We sit at the frontier of enterprise AI — combining structured ontological knowledge with the expressive power of foundation models to build Q&A systems that are both intelligent and trustworthy. Join a passionate team of engineers and researchers pushing the boundaries of neuro-symbolic AI at scale.

Your set of application documents should contain a cover letter, a resume in table form, school leaving certificates, certificate of enrollment, current university transcript of records, copies of any academic degrees already earned, and if available, references from former employers (including internships). Please also describe your experience and skills in foreign languages and computer programs / programming languages.