Postdoctoral Appointee - Artificial Intelligence Infrastructure - Hybrid

About Sandia

Sandia National Laboratories is the nation’s premier science and engineering lab for national security and technology innovation, with teams of specialists focused on cutting‑edge work in a broad array of areas. Some of the main reasons we love our jobs:

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Sandia's artificial intelligence (AI) team is building the U.S. Department of Energy's (DOE) next‑generation AI Platform, an integrated scientific AI capability that delivers rapid, high‑impact solutions for national security, science, and applied energy missions. The Platform is based on three pillars:
Models, Infrastructure, and Data. As a Postdoctoral Appointee, you will join the Infrastructure Pillar team to design, develop, and deploy the unified compute‑and‑data fabric that underpins all mission workflows; from AI model training and simulation steering to real‑time inference at experimental and production facilities.

We anticipate multiple hires for the Infrastructure Pillar that collectively span the set of responsibilities and skills described below. Likewise, postdoctoral appointees will be expected to work in conjunction with their Sandia mentors and teams from across Sandia and other DOE laboratories to deliver on this ambitious, fast‑paced project. Importantly, we anticipate that while AI Platform development will leverage existing AI and data science tools extensively, success will also require deep technical insights, considerable innovation, research, and problem solving to address the unique needs of DOE applications.

If this sounds like an exciting challenge to you, we look forward to reading your application!

• Architect and implement the hybrid compute fabric
• Integrate exascale HPC systems with elastic cloud resources and specialized AI accelerator clusters (on‑prem and in‑cloud)
• Deploy ruggedized edge servers and digital‑twin
• Infrastructure for sub‑millisecond inference and real‑time physics simulations
• Develop software infrastructure for agentic workflows integrating modeling and simulations with real‑time inference
• Build federated Kubernetes clusters, container registry services, resource registry, and job scheduling abstractions
• Design secure networking and enclaves and evaluate federated training frameworks on secure networks
• Enable observability, provenance, and monitoring
• Provide software‑defined, dynamic security enclaves for sensitive data with attested runtime and curated egress
• Deploy unified logging, metrics, dashboards, and trace‑analysis across cloud and on‑prem environments using Open Telemetry, Prometheus, ELK, or equivalent
• Support federated identity and access control
• Integrate multiple identity providers, attribute‑based access controls, and allocation models for risk‑shared governance
• Manage enterprise licensing, token agreements, and software audits for AI and HPC frameworks
• Manage the full lifecycle of the AI platform's infrastructure, including capacity planning, upgrades, documentation, and performance monitoring
• Implement and enforce security best practices within container environments, including Role‑Based Access Control (RBAC), secrets management, network policies, and vulnerability scanning

• Stand up a new GPU‑accelerated cluster, configure Slurm/Kubernetes, and validate performance benchmarks
• Troubleshoot…