You’ll work at the intersection of advanced AI research, enterprise applications, and real-world problem solving, partnering closely with internal teams and model researchers to evaluate and improve high-value use cases.
In this applied, hands‑on role, you’ll analyze challenging use cases across the organization, understand their business context, and help push our tabular foundation models to their full potential. Through debugging, benchmarking, and deep technical iteration, you’ll uncover patterns, limitations, and opportunities, and turn them into actionable insights that directly inform model research and model architecture improvements.
You’ll collaborate deeply with application teams and domain experts, serving as a bridge between practical use‑case execution and ongoing model research. Your input will have a direct impact on how our models evolve and how effectively they perform on meaningful enterprise problems.
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 developing predictive use cases on tabular data in a data scientist role, ideally with S/4HANA data.
Deep mastery of deep learning and Transformer architectures, including application to structured enterprise data, along with strong software engineering skills in Python and a proven track record of building and scaling experiments with PyTorch or TensorFlow.
Strong communication and collaboration skills, with the ability to work effectively in cross‑cultural teams.
SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are in need of accommodations or special assistance, please send an e‑mail with your request to Recruiting Operations Team:
#J-18808-LjbffrVeröffentlichungsdatum:
29 Apr 2026Standort:
Garching bei MünchenEinsatzort:
Walldorf, GermanyTyp:
VollzeitArbeitsmodell:
Vor OrtKategorie:
Erfahrung:
2+ yearsArbeitsverhältnis:
Angestellt
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