Lawrence Livermore National Laboratory (LLNL) is hiring a Data Science Engineer

We have multiple openings for early-career Data Science Engineers to join a team applying machine learning, AI/NLP, and data science to national security challenges. You will contribute to the design, development, and deployment of AI-driven capabilities — including large language models (LLM)-based pipelines, knowledge graphs, and intelligent agent prototypes — that advance data and decision sciences for national security. Working alongside senior engineers and domain experts, you will write production-quality code, help build analytical tools and visualizations, and contribute fresh ideas to challenging problems. These positions are in the Computational Engineering Division (CED), within the Engineering Directorate, in support of impactful Global Security Directorate missions. Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week. You will - Under the guidance of senior team members, apply machine learning and data science algorithms to help analyze national security datasets. - Contribute to LLM-driven data pipelines for information extraction, entity resolution, and automated analysis of large-scale structured and unstructured datasets. - Help build and maintain knowledge graphs and graph-based analytics (e.g., graph-RAG) to model relationships across national security domains. - Assist in prototyping AI agents and conversational interfaces that allow analysts to query data science capabilities through natural language. - Write clean, well-documented code to implement data science solutions, create visualizations, and support analytical tools, following software engineering best practices for version control, testing, and documentation. - Collaborate with multidisciplinary teams including intelligence analysts, domain scientists, and computer scientists in building research prototypes and capabilities. - Contribute to technical reports, internal presentations, and peer-reviewed publications and conference papers. - Perform other duties as assigned.