Materials Scientist/Engineer - Advanced Materials Processing and Digital Infrastructure – Active Clearance Required

Join us and make YOUR mark on the World! Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability. Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact. We have an opening for a Materials Scientist/Engineer to lead the development and implementation of advanced manufacturing processes, data infrastructure, and inspection technologies that accelerate R&D workflows and support programmatic objectives. You will work at the intersection of materials science, process engineering, data systems, and experimental validation, providing technical leadership on complex, high-visibility efforts that span multiple organizations and stakeholder groups. You will direct technical strategy for advanced manufacturing initiatives, coordinate multi-site collaborations, and serve as a primary technical contact for projects that support Laboratory mission focus areas and sponsor priorities. This position is in the Materials Engineering Division (MED) within the Engineering Directorate. 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 Lead the technical execution and strategic direction of advanced manufacturing process development, inspection technology maturation, and data infrastructure initiatives that support multiple programs and organizational objectives. Develop and implement innovative technical approaches that integrate experimental processes, inspection systems, and data management platforms to solve highly complex problems with