SAP Master Thesis Student (f/m/d) - RAG Pipeline Optimization

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About the SAP Internship Experience Program: 

The SAP Internship Experience Program is SAP’s global, strategic, paid internship program that provides university students with opportunities to find purpose in their careers. 

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About the team: 

Within SAP Labs Munich, the Industry-University Collaboration Hub team focuses on applied research, knowledge exchange, and co-innovation with universities, especially TU Munich, to create positive economic and social impact.

What you´ll do:

Position title: SAP Master Thesis Student (f/m/d) - RAG Pipeline Optimization
Work Area: Software-Research 
Location: Munich
Expected start date: 01. July, 2025

RAG is widely used to improve large language modeling performance by combining information retrieval with generative capabilities. However, optimizing such pipelines—particularly the selection and tuning of components like retrievers, filters, and generators, remains a complex task. This thesis aims to investigate the integration of Bayesian Optimization (BO) into the RAG pipeline to automate and accelerate RAG pipeline optimization. We will explore the dual role of BO in both discrete module selection and continuous hyperparameter tuning. Through a series of research questions, we will examine the robustness of BO under varying data quality, domain shifts, and computational constraints. Our work will leverage state-of-the-art optimization libraries and provide insights into making RAG pipeline more efficient, adaptable, and domain-aware.
 

About the project: 

Title: Leveraging Bayesian Optimization for Accelerating RAG Pipeline Optimization

Objective: Integrate Bayesian Optimization (BO) into RAG pipeline to optimize Retrieval-Augmented Generation (RAG) pipelines.

Research Questions: 

1. Scope of BO: Can BO effectively select RAG components (e.g., retrievers, filters) and tune them?
2. Trade-Offs: How do constraints like time, compute, or evaluation budget impact BO performance?
3. Data-Impact: How sensitive is BO to the size/quality of the evaluation dataset?
4. Outcome Robustness: Are the results consistent across domains and query types?

Who you are: 

You are a student (f/m/d) at a university or a university of applied sciences. We’re looking for someone who takes initiative, perseveres, and stays curious. You like to work on meaningful innovative projects and are energized by lifelong learning. 

• Language: German at B2-level is mandatory
• Programming Language: Python
• Version Control: Git
• Bayesian Optimization Libraries: SMAC3, BOHB, or RayTune
• Machine Learning & NLP:Understanding of how RAG pipelines function
• Pipeline Optimization: Experience in automating ML pipeline configuration/tuning

Visit our Careers Page for more information on the program. 

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. 

Note for Germany: currently the SAP Internship Experience Program is only open to interns and being hired into other contract types such as working students will preclude the candidate's participation in the program.  

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Requisition ID: 426641  | Work Area: Software-Research  | Expected Travel: 0 - 10%  | Career Status: Student  | Employment Type: Limited Full Time   | Additional Locations: #LI-Hybrid