Data Scientist — Graph ML & RAG (Hybrid)

SAP SE; Palo Alto (CA); Hybrid; USD 175,000 - 206,000; Full time

Job summary

SAP SE is seeking a Data Scientist at our Palo Alto, CA location to develop and optimize ML models and research AI solutions. You will collaborate with cross-functional teams to translate business problems into ML workflows and deliver scalable, explainable AI systems.

Applicants should have advanced degrees in CS/Engineering and hands-on experience with knowledge graphs, graph-based ML, and RAG pipelines. This hybrid role emphasizes strong communication and problem solving in a fast-paced

Qualifications

• Bachelor's degree or foreign equivalent in Computer Science, Engineering, or a related field of study and five (5) years of progressive post-baccalaureate experience in the job offered or related occupation.
• Alternatively, a Master’s degree or foreign equivalent in Computer Science, Engineering, or a related field of study and three (3) years of experience in the job offered or related occupation.

Responsibilities

• Support machine learning research/project and development teams with all aspects around AI algorithms.
• Design and implement novel machine learning algorithms to process real data.
• Apply recent research breakthroughs to real problems to create business value.
• Ensure explainability and ethical integrity of AI algorithms.
• Communicate the relevance of implemented systems and achieved results in a visual and consistent way.

Skills

Knowledge graphs

Graph ML models

LLM fine-tuning

AI research & publishing

Education

Bachelor's or Master's in CS/Engineering or related field

Tools

Azure ML

Databricks

Job description

SAP SE is seeking a Data Scientist at our Palo Alto, CA location to develop and optimize ML models and research AI solutions. You will collaborate with cross-functional teams to translate business problems into ML workflows and deliver scalable, explainable AI systems.

Applicants should have advanced degrees in CS/Engineering and hands-on experience with knowledge graphs, graph-based ML, and RAG pipelines. This hybrid role emphasizes strong communication and problem solving in a fast-paced