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 Bosch Home Comfort Group is looking forward to your application!
Job Description
During your assignment, you will collect, structure and preprocess engineering knowledge sources such as technical documents, specifications, test reports and structured datasets.
You will evaluate suitable Databricks-native and open-source tools (e.g. RAG, Text-to-SQL, AI Agents, Vector Search, Genie) for different types of engineering content.
Based on this, you will design and implement natural language workflows on Databricks that allow hardware engineers to query both documents and structured data.
To deliver reliable, source-grounded answers, you will apply prompt and context engineering and ensure result quality and traceability (e.g. citations, evaluation, guardrails).
Additionally, you will collaborate closely with hardware engineers to understand use cases and iteratively improve the solution.
Finally, you will communicate progress and findings through visualizations, short presentations and technical documentation.
Qualifications
Education: master studies in the field of Data Science, Artificial Intelligence, Computer Science, Information Systems, Engineering or a comparable quantitative or technical area with good grades
Experience and Knowledge:
practical knowledge of large language models and Generative AI concepts such as RAG, embeddings, vector databases, prompt and context engineering, or AI agents
solid programming skills, ideally in Python and SQL
engineering background as a plus
experience with Databricks (e.g. Vector Search, Genie, Mosaic AI Agent Framework, MLflow), LangChain, LlamaIndex or other Generative AI frameworks as an advantage
understanding of heat pump technology and operating principles as an asset
Personality and Working Practice: you are curious and self-driven, bringing a structured approach and strong communication skills to engaging with engineers from different backgrounds, understanding their needs and translating them into technical solutions
Work Routine: we offer you the opportunity to work in a hybrid setup with regular on-site presence
Enthusiasm: passionate about bridging AI and hardware engineering and making complex technical knowledge easily accessible through natural language
Languages: very good in English
Additional Information
Start: according to prior agreement
Duration: 6 months
Requirement for this internship is the enrollment at university. Please attach your CV, transcript of records, enrollment certificate, 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?
Linnan Du (Functional Department)
+49 7153 306 8232
Work #LikeABosch starts here: Apply now!
#LI-DNI
Summary
Build natural language workflows on Databricks that let hardware engineers query documents and structured data using RAG, Text-to-SQL and AI agents for source-grounded answers. Requires enrollment in a master's program in data science, AI, computer science or engineering, practical large language model knowledge, and solid Python and SQL skills.
Responsibilities
Collect, structure and preprocess engineering knowledge sources; evaluate Databricks-native and open-source tools; design and implement natural language workflows; apply prompt and context engineering with citations, evaluation and guardrails; collaborate with hardware engineers; communicate findings via visualizations and documentation
Qualifications
Master studies in Data Science, AI, Computer Science, Information Systems, Engineering or comparable field with good grades; very good English; curious, self-driven, strong communication skills
Education requirements
Master studies in Data Science, AI, Computer Science, Information Systems, Engineering or comparable quantitative or technical area with good grades; enrollment at university
Experience requirements
Practical knowledge of LLMs and generative AI concepts (RAG, embeddings, vector databases, prompt and context engineering, AI agents); solid Python and SQL programming; engineering background a plus
How to apply
CV, transcript of records, enrollment certificate, examination regulations; valid work and residence permit if indicated