Senior​/Principal AI Researcher; CA), Onsite

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:

• Challenging work with amazing impact that contributes to security, peace, and freedom worldwide
• Extraordinary co‑workers
• Some of the best tools, equipment, and research facilities in the world
• Career advancement and enrichment opportunities
• Flexible work arrangements for many positions include 9/80 (work 80 hours every two weeks, with every other Friday off) and 4/10 (work 4 ten‑hour days each week) compressed workweeks, part‑time work, and telecommuting (a mix of onsite work and working from home)
• Generous vacation, strong medical and other benefits, competitive 401k, learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance*

World‑changing technologies. Life‑changing careers. Learn more about Sandia at: http://(Use the "Apply for this Job" box below)..gov

* These benefits vary by job classification.

The Data Sciences and Computing team seeks R&D AI Engineer to develop next‑generation science & engineering AI capabilities that accelerate our national security missions. In this role, you will lead and contribute to research, development, and deployment of high‑impact AI models and algorithms, spanning large reasoning models, graph‑based and network‑science methods, high‑fidelity surrogate modeling for multi‑physics simulations, and agentic workflows that orchestrate complex computational and experimental pipelines.

Your work will emphasize rigor, scalability, reliability, and security, enabling scientists and engineers to explore complex design spaces, analyze scenarios and data, and engineer solutions faster and with higher assurance.

You will join a collaborative research team working at the nexus of predictive simulation models and secure/reliable AI. Team expertise includes data science, artificial intelligence, mathematics/statistics, computer science, computational science & engineering, and high‑performance computing. You will partner with scientists and engineers spanning myriad domains to formulate and solve challenging problems across our security, science, and engineering missions.

We anticipate multiple hires that collectively span the set of responsibilities and skills described below. If this sounds like an exciting challenge to you, we look forward to reading your application!

On any given day, you may be called on to:

• Research and develop advanced AI models, e.g., LLMs, VLMs, GNNs, or general foundation models, and tailor them to domains such as physical sciences, network analysis, or cyber‑physical security.
• Judiciously fuse physics‑based and data‑driven models in surrogate, SciML, or multi‑fidelity approaches, e.g., to accelerate multi‑physics or network science simulations, enable efficient data assimilation, and construct digital twins.
• Architect and implement efficient, credible, and transparent multi‑agent / agentic systems for complex analysis, simulation, and/or data gathering workflows.
• Perform exploratory data analysis, data/feature engineering, and machine learning for trend analysis, anomaly detection, or attribution.
• Develop scalable algorithms for networks and other graph‑structured data to enable efficient exploration of large, complex datasets.
• Research and develop approaches to evaluate and improve AI security, reliability, and credibility, including assurance, benchmarking, counter‑adversarial AI/ML, red‑team, explainability, and UQ methods.
• Integrate AI/ML and Mod Sim into all phases of the engineering lifecycle, including requirements derivation/management, trade space exploration, design, analysis, manufacturing, and qualification.
• Conduct fundamental research in mathematical, computer, and data sciences as needed to support the above activities.
• Develop open‑source and proprietary software toolkits using modern software engineering practices and integrate them into domain‑specific applications.
• Utilize various computing platforms including traditional, high‑performance,…