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or coursework involving natural language processing (NLP) or large language models (LLMs). Familiarity with embeddings, prompt development, semantic search techniques, or vector databases. Exposure to retrieval
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for raster and vector data (projection harmonization, spatial joins, tiling/chunking, and QA/QC). Develop geospatial validation frameworks for model outputs (e.g., comparisons to reference datasets, spatial
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, a strong emphasis in delighting customer and end-user needs. Preferred Qualifications: Active DOE Q clearance. Understanding of multidimensional and tabular modelling, vector databases, Graph DB
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, a strong emphasis in delighting customer and end-user needs. Preferred Qualifications: Active DOE Q clearance. Understanding of multidimensional and tabular modelling, vector databases, Graph DB