About the role
AI summarisedThe Senior Data Scientist at GE Aerospace will design and develop LLM/GenAI solutions for documentation-driven use cases such as search, Q&A, information extraction, summarization, and report generation. They will build document and RAG pipelines, integrate AI services into digital inspection applications and shop-floor tools, and collaborate with domain experts to translate workflows into AI use cases. The role emphasizes responsible AI use with appropriate guardrails, grounding, and documentation to support safety, quality, and governance in aerospace inspection and engineering workflows.
AerospaceOnsiteDigital Technology / IT
Key Responsibilities
- Design and develop LLM/GenAI solutions for documentation-driven use cases (search & Q&A, information extraction, summarization, report generation, assistant‑style tools for inspectors and engineers)
- Build document and RAG pipelines, including ingestion, processing and indexing of e‑manuals, shop documents and other unstructured data
- Collaborate with data engineers and application teams to integrate LLM/GenAI services into digital inspection applications, portals and shop‑floor tools
- Work closely with domain experts to understand workflows and pain points, translate them into AI use cases, and drive PoCs and pilots to production
- Ensure responsible and compliant use of LLM/GenAI, including appropriate guardrails, grounding, and documentation to support safety, quality and governance requirements
Requirements
- Master’s or PhD in Computer Science, Electrical/Computer Engineering, Artificial Intelligence, Applied Mathematics, Statistics, or a related quantitative field
- Bachelor’s degree in a relevant discipline with strong, proven industry experience in computer vision, deep learning or industrial inspection
- Additional coursework, certifications or research experience in natural language processing, information retrieval, machine learning or software engineering
- 5+ years of hands‑on data science, NLP or AI application development
- Solid understanding of NLP/LLM & GenAI techniques, such as text classification, information extraction, question answering, summarization, prompt engineering, RAG and evaluation of language models
- Strong programming skills in Python, with experience using relevant libraries and frameworks (e.g. PyTorch / TensorFlow, Hugging Face, LangChain/LlamaIndex, spaCy, FastAPI)
- Familiarity with cloud and data platforms (e.g. Databricks, AWS, Azure, vector databases, search engines)
- Strong cross‑functional collaboration, problem‑solving, and influencing skills
- Comfortable working in an ambiguous, fast‑evolving environment