AI Infrastructure and Advanced Computing Scientist; Scientist

Help shape the AI and advanced-computing capabilities that enable scientific discovery and national-security missions. The Applied Computer Science Group (CAI-1) is seeking a Scientist 3/4 to provide technical leadership across emerging-computing testbeds, institutional AI infrastructure, and applied-AI projects.

In this role, you will combine hands‑on technical work with cross‑organizational leadership. You will evaluate new computing technologies, develop secure and scalable AI services, and help Laboratory teams turn promising AI concepts into useful, sustainable capabilities.

You will:

• Lead the integration and evaluation of emerging computing architectures, accelerators, and software stacks for scientific simulation, data analysis, and AI.
• Architect and mature AI services that span model serving, retrieval and agentic workflows, GPU resources, orchestration, observability, and on-premises or cloud environments.
• Develop reproducible experiments and benchmarks to assess performance, scalability, reliability, usability, cost, and mission suitability.
• Partner with researchers, computing operations, cybersecurity organizations, and vendors to define requirements, resolve technical risks, and move prototypes into reliable use.
• Strengthen applied-AI delivery through technical consultation, project triage, reusable components, documentation, training, mentoring, and effective handoff to mission teams.

This position may be filled at either the Scientist 3 or Scientist 4 level, depending on the selected candidate's qualifications.

At the Scientist 3 level, you will lead major technical efforts and multidisciplinary project teams.

At the Scientist 4 level, you will serve as a Laboratory‑level technical authority, establish strategy and architecture across organizations, and build institutional capabilities and programs.

Minimum

Job Requirements:

• Technical expertise:
  Advanced knowledge in one or more relevant areas, such as AI/ML systems, high‑performance computing, computer architecture, distributed systems, accelerated computing, cloud‑native platforms, or scientific software infrastructure.
• Systems development and integration:
  Demonstrated experience developing, integrating, or evaluating complex computing systems in Linux environments, including multiple layers such as compute, storage, networking, containers, orchestration, schedulers, model runtimes, data services, or monitoring.
• Experimental evaluation:
  Experience designing reproducible computational experiments, analyzing performance or system behavior, and using results to guide architecture or technology decisions.
• Technical leadership:
  Demonstrated ability to lead complex technical projects, establish scope and priorities, coordinate multidisciplinary contributors, manage risks, and deliver results; experience mentoring staff or students.
• Collaboration and communication:
  Ability to work effectively across research, operational, security, and program organizations and communicate technical findings, tradeoffs, and recommendations through clear writing and presentations.

• Institutional impact:
  Significant technical achievements that have advanced AI, computing, research, or mission capabilities at a Laboratory‑wide or comparable institutional scale.
• Technical strategy:
  Demonstrated experience establishing architectures, standards, roadmaps, or investment direction for complex computing capabilities.
• Cross‑organizational leadership:
  Success leading large, multidisciplinary, high‑risk efforts and serving as an authority for consequential technical decisions.
• Capability development:
  Demonstrated success building teams,…