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This project aims to utilize LLMs (Large Language Models) to enhance the usability of systems engineering documentation, including system requirement documents and flowdowns, interface documents, design documents, and reliability assessments. The objective is to develop an LLM-based tool that can identify conflicting documents and requirements, as well as summarize large volumes of documentation to provide specific answers to targeted questions. Privacy is a crucial aspect, as all documents must remain within a local private network/server to ensure data confidentiality.

1. Proficiency in utilizing LLMs for systems engineering documentation analysis.

2. Understanding of various types of systems engineering documentation.

3. Enhanced analytical skills in identifying conflicts and inconsistencies.

4. Ability to summarize complex information effectively.

5. Knowledge of data privacy and security considerations in document analysis.

Experience in Python is required, and experience in instrumentation and/or machine learning is valued.