Job DescriptionWe have an opening for a Materials Research Staff Member to lead the development and institutionalization of advanced data, AI, automation, and digital infrastructure capabilities that accelerate R&D workflows across materials engineering and science environments. You will work at the intersection of materials research, hardware automation, AI, data engineering, cloud and internally hosted computing systems, and institutional data infrastructure, helping define and deploy scalable technical solutions for Lab-wide adoption.
You will lead and coordinate multidisciplinary efforts spanning Engineering, Science and Technology, Computing, Enterprise Networking, cybersecurity, and institutional data governance bodies, while collaborating with internal and external partners to modernize how experimental, process, and machine data are captured, governed, integrated, and used for AI-enabled scientific workflows. This position is in the Materials Engineering Division (MED) within the Engineering Directorate.
This position requires full-time on-site presence due to the nature of the work.
You will - Lead the research, design, validation, and transition of advanced R&D data and AI workflow technologies for institutional deployment.
- Architect and implement integrated technical solutions for scientific data workflows, metadata capture, automation systems, and AI-enabled experimental environments.
- Develop and drive institutional standards, frameworks, and infrastructure for AI and automation networking, metadata management, and data lake architectures for the Materials Engineering Division and beyond.
- Resolve complex technical objectives involving competing requirements across scientific workflows, enterprise IT, cybersecurity, data governance, and sponsor needs.
- Serve as a primary technical leader on projects focused on modernizing R&D workflows through data engineering, AI integration, hardware automation, and scalable compute and storage architectures.
- Define technical requirements, system architectures, and implementation strategies that support cross-directorate and cross-site scientific collaboration.
- Collaborate with technical area leaders, project leaders, program management, IT partners, and institutional governance organizations to align solutions with broader Laboratory priorities.
- Represent technical capabilities, architectures, and project outcomes to internal management, institutional leadership, and external sponsors.
- Organize, analyze, and present technical results, adoption outcomes, and workflow impacts from research and development activities.
- Contribute to the conception, design, and execution of innovative projects that advance institutional data and AI capabilities for R&D environments.
- Mentor early-career staff in data engineering, software architecture, automation systems, AI-enabled workflows, and hardware integration.
- Publish research and technical results, present at technical meetings, and contribute to strategic proposals and institutional initiatives.
- Apply technical knowledge and methodologies to guide the successful completion of project and organizational goals, serving as the primary technical contact on tasks and projects.
- Perform other duties as assigned.
Qualifications- This position requires an active Department of Energy (DOE) Q-level clearance or an active Top Secret clearance issued by another U.S. government agency at the time of hire.
- Bachelor's degree in Computer Engineering, Materials Science and Engineering, Mechanical Engineering, or a related technical field, or an equivalent combination of education and relevant experience.
- Significant experience developing and leading advanced technical work in one or more of the following areas: scientific data engineering, R&D workflow architecture, AI-enabled experimental systems, laboratory automation, metadata systems, cloud and on-premises data infrastructure, or distributed computing environments.
- Experience leading complex technical efforts that span multiple organizations and require coordination across scientific, engineering, IT, and operational stakeholders.
- Experience architecting and implementing data pipelines, workflow systems, or technical platforms for scientific, engineering, or experimental environments.
- Ability to define technical strategy, resolve complex and sometimes competing requirements, and independently pursue solutions with consultative direction.
- Experience serving as a primary technical contact on projects and representing technical approaches and outcomes to management, sponsors, and cross-functional stakeholders.
- Advanced verbal and written communication skills necessary to present, explain, and advise on complex technical topics.
- Ability to mentor personnel and contribute to a collaborative, multidisciplinary team environment.
Qualifications We Desire- Advanced degree in Computer Engineering, Materials Science and Engineering, Mechanical Engineering, or a related technical field.
- Experience designing and institutionalizing AI-enabled R&D workflows that integrate hardware systems, automation platforms, and modern data infrastructure.
- Experience developing metadata architectures, data catalogs, or data governance-aligned scientific data systems.
- Experience with cloud platforms, hybrid compute environments, and data lake architectures for scientific or engineering applications.
- Experience with networking, system integration, and secure infrastructure approaches that support automated or AI-enabled laboratory workflows.
- Experience with programming and scripting languages such as Python, MATLAB, LabVIEW, C/C++, or related technologies.
- Experience designing software and hardware integrations for benchtop instrumentation, automation systems, and edge compute environments.
- Experience contributing to institutional initiatives, cross-directorate strategy, or external sponsor-facing technical activities.
Pay Range$210,630 - $267,060 Annually
This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage. An employee's position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.
Additional Information#LI-Onsite
Position InformationThis is a Career Indefinite position, open to Lab employees and external candidates.
Security ClearanceThis position requires an active Department of Energy (DOE) Q-level clearance or active Top Secret clearance issued by another U.S. government agency at time of hire.
