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Master Thesis LLM-based Co-pilot for the ECU Test Development

Robert Bosch Group

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On-site
EUR 40,000 - 60,000
30+ days ago
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Master Thesis LLM-based Co-pilot for the ECU Test Development
Robert Bosch Group
Renningen
On-site
EUR 40.000 - 60.000
Full time
30+ days ago

Job summary

A technology company in Germany seeks a Master student for a thesis project focused on developing an intelligent assistant for Electronic Control Unit testing. This role integrates programming expertise with LLMs to streamline workflows. Applicants should have strong Python skills, relevant academic qualifications, and should be self-motivated. The position offers a duration of 6 months and requires university enrollment.

Qualifications

  • Strong intrinsic motivation and ability to work independently.
  • Very good grades in relevant studies.

Responsibilities

  • Design and implement an intelligent assistant system for ECU test development.
  • Integrate LLMs with current engineering tools.
  • Enhance productivity and improve quality of test development.

Skills

Programming skills in Python
Experience with LLMs
Knowledge of MCP, RAG, and Agentic Frameworks
Experience with User Interface, Backend and FastAPI
Fluent in English

Education

Master studies in Computer Science, Mathematics, Statistics or comparable
Job description

Company Description

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.

The Robert Bosch GmbHis looking forward to your application!

Job Description

Developing production tests for Electronic Control Units (ECUs) is a complex and time-consuming task. It requires domain engineers to manually extract, verify and consolidate information from a wide range of heterogeneous sources, including technical documents, spreadsheets and specialized databases. This process is not only tedious but also prone to errors due to the unstructured and fragmented nature of the data.

  • The goal of your Master thesis project is to design and implement an intelligent assistant system that will support domain engineers throughout the ECU test development workflow.
  • The envisioned system will integrate large language models (LLMs)-based techniques with existing engineering and software development tools to create context-aware co-pilot that can assist in retrieving relevant parameters, interpreting technical content and streamlining test creation.
  • By leveraging the capabilities of LLMs, the system aims to enhance productivity, reduce manual effort, and improve the overall quality of the test development process.
Qualifications
  • Education: Master studies in the field of Computer Science, Mathematics, Statistics or comparable with very good grades
  • Experience and Knowledge: strong programming skills in Python; experiences with LLMs, MCP, RAG and/or Agentic Frameworks; experience with User Interface, Backend and FastAPI is an advantage
  • Personality and Working Practice: you excel at working independently and driving your own projects forward with strong intrinsic motivation
  • Languages: fluent in English
Additional Information

Start:according to prior agreement
Duration:6 months

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?
Daria Stepanova (Functional Department)
+49 173 468 3722

#LI-DNI

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* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.

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