Master Thesis in Graph-based Retrieval Augmented Generation - remote possible
Master Thesis in Graph-based Retrieval Augmented Generation - remote possible
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Job Description
- During your assignment you will migrate the existing RAG solution to an agentic graphbased framework (e.g. LangGraph) and optimize the architecture for enhanced modularity and scalability.
- To optimize performance you will develop and implement graphbased techniques to improve retrieval accuracy and output relevance.
- You will build APIs to enable seamless integration of the RAG system with external tools and platforms facilitating broader adoption.
- Furthermore you will oversee the deployment of new solution versions implement continuous monitoring frameworks and track quality metrics to ensure improvements align with stakeholder expectations.
- Finally you will integrate additional structured and unstructured data sources into the graphbased framework to enhance the systems knowledge base.
Qualifications :
- Education: Master studies in Computer Science Data Science or comparable
- Experience and Knowledge: proficiency in Python; ideally some experience in building RAG systems or Chatbots
- Personality and Working Practice: selfdriven individual with a strong passion for developing the best possible solutions combining independent work ethic with a proactive and solutionoriented mindset
- Work Routine: mobile working within Germany
- Languages: fluent in English
Additional Information :
Start: according to prior agreement
Duration: 6 months
You want to work flexibly from your home in Germany or prefer working at the Bosch location in Abstatt
For positions with the addition remote possible you can agree on the appropriate collaboration for your task together with your manager and your team within the framework of Smart Work.
Requirement for this thesis is the enrollment at university. Please attach your CV transcript of records examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.
Need further information about the job
Simon Klug (Functional Department)
#LIDNI
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
