Experienced AI Credibility Researcher - Onsite

Experienced AI Credibility Researcher - Onsite

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.

• Lead and contribute to interdisciplinary technical teams conducting creative research in elements of AI modeling, development, and credibility.
• Help define research directions, technical strategy, and long‑term vision for credible AI in national security and high‑consequence scientific settings.
• Develop advanced research ideas that address challenging Sandia mission problems and craft those into original research proposals.
• Publish technical results in peer-reviewed venues, contribute to internal technical reports, and present findings to research, program, and leadership audiences.
• Serve as a strategic leader to develop funding opportunities, identify research directions, and grow a new team in the field of AI Credibility.
• Apply AI tools integrated with enabling credibility processes to advance Sandia's national security missions.
• Mentor junior researchers and contribute to the growth of a vibrant research community in trusted and credible AI.

• Foundations of AI Credibility, including evaluation, assurance, and trustworthiness for AI‑enabled systems.
• Methods in verification, validation, uncertainty quantification, and robustness for machine learning and generative AI models.
• AI model performance under distribution shift, sparse data, rare events, and other high‑consequence operating conditions.
• Interpretable, explainable, and transparent AI to support scientific understanding and defensible use of model outputs.
• Human‑AI teaming, including trust calibration, uncertainty communication, and effective oversight in expert decision environments.
• Approaches to data quality, provenance, reproducibility, and traceability in AI workflows.
• Credibility of foundation and generative models, including grounding, factuality, hallucination mitigation, and evaluation of emergent behaviors.
• Physics‑informed AI, hybrid modeling, and constrained learning approaches for mission‑relevant applications.
• Methods for analyzing, representing, and understanding complex and large datasets, both enabling and enabled by AI.
• Benchmarks and frameworks for AI test and evaluation, assurance cases, and evidence-based model assessment.

You will be part of a multidisciplinary, research‑and mission‑focused team developing foundational research directions in AI Credibility to support Sandia's national security and nuclear deterrence mission areas. Occasional travel may be required.

Due to the nature of the work, the selected applicant will be required to work onsite. Relocation will be provided for those that qualify.

$138,600 - $235,700

* Salary range is estimated, and actual salary will be determined after consideration of the selected candidate's experience and qualifications, and application of any approved geographic salary differential.

A Bachelor's degree in a relevant discipline and five (5) years of directly relevant experience, or an equivalent combination of directly relevant education and engineering or scientific experience that demonstrates the knowledge, skills, and ability to perform independent research and development.

Ability to obtain and maintain a DOE Q clearance.

The ideal R&D S&E candidate for AI Credibility Sandia National Laboratories will in addition possess the following:

• Graduate degree in a relevant computationally-intensive discipline where an independent research project was a graduation requirement (e.g., independent project, thesis, or dissertation).
• Experience in developing software and AI systems for enterprise and national security applications.
• Demonstrated software development skills and familiarity with modern software development practices.
• Proven ability to work and communicate effectively in a collaborative and interdisciplinary team environment.
• Experience teaming in an interdisciplinary R&D setting, including the proven ability to collaborate on…