Senior/Principal Secure AI Algorithms, Hybrid

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
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• 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://www.sandia.gov

*These benefits vary by job classification.

We are seeking R&D Secure AI Algorithms staff (job title: R&D AI). Sandia's Secure Algorithms team is advancing adoption and use of AI for Laboratory mission needs. The advances are to develop and evaluate scientific AI capability itself for security and reliability, and deliver aware and resilient AI-based solutions for national security, science, and applied energy missions. You will join the team to architect, develop, and deploy mathematically rigorous reasoning models, as well as scalable graph and network analysis algorithms, and autonomous agent orchestration for complex workflows. Expertise in graph theory, combinatorics, and network science techniques will enable scientists and engineers to explore complex design spaces, evaluate interconnected outcomes, and steer experiments and simulations with transparent, high-assurance reliable AI.

While AI development leverages existing AI and data science tools, success will require innovative mathematical modeling, algorithmic problem solving, and high-performance computing expertise tailored to the unique needs of DOE applications.

Key Responsibilities:

• Research, develop, and fine-tune advanced graph-based reasoning models (e.g., graph neural networks, spectral methods, combinatorial optimization) for domain tasks in the Physical Science and Cyber
• Design scalable algorithms and mathematical frameworks for network analysis that enable efficient exploration of large, complex scientific datasets and simulations
• Develop and apply network science techniques for counter-adversarial community detection
• Develop domain foundation models incorporating graph-structured data from DOE simulations, experiments, and production systems
• Build high-fidelity surrogate models and scalable graph-based approximations to accelerate exascale multiphysics simulations, leveraging expertise in high-performance and parallel computing on large clusters
• Architect multi-agent frameworks with transparent decision graphs, uncertainty quantification, and auditability, leveraging mathematical rigor in graph theory and network dynamics
• Embed continuous learning pipelines that integrate model training and evaluation with live telemetry from HPC clusters, experiments, and autonomous labs
• Establish robust model repositories with metadata, software bill of materials (SBOMs), versioning, drift/poisoning surveillance, and periodic recertification
• Implement high-assurance controls for sensitive workloads
• Contribute to open-source and internal AI frameworks, toolkits, and best practices for agentic workflows grounded in mathematical theory and scalable computation
• Demonstrate strong teamwork, collaboration, and communication skills, including experience presenting research findings to diverse audiences and contributing to peer-reviewed publications

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

• Prototype custom graph neural networks or scalable spectral algorithms for multisensor fusion in agile-deterrence scenarios using C++ and Python
• Optimize surrogate neural networks or graph-based approximations to replace costly physics submodules in design simulations, leveraging parallel computing techniques on large clusters
• Design Planner agents that orchestrate HPC jobs, digital-twin simulations, and robotic chemistry runs using graph-based decision frameworks
• Conduct red-team evaluations to stress-test foundation models for adversarial robustness and fairness, focusing on graph-structured data vulnerabilities and adversarial-aware techniques
• Package models into containers with Kubernetes operators for deployment in classified enclaves
• Advise domain scientists on prompt engineering, model-based hypothesis generation, and mathematical modeling of complex networks
• Present prototype demos and research results to stakeholders across DOE, DoD, IC, and industry, utilizing strong teaching and public speaking skills

The selected applicant may engage in a combination of onsite and offsite work. The selected applicant must live within a reasonable distance for commuting to the assigned work location when necessary.

$139,900 - $280,600

*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-level security clearance.

The ideal R&D S&E Artificial Intelligence candidate for 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.

Also, for this posting we are seeking individuals with the following experience:

• Fluency in programming languages including C/C++ and Python
• Experience with high-performance and parallel computing on large clusters
• Demonstrated ability to design and implement scalable algorithms for complex scientific datasets and simulations
• Strong foundation in graph theory, combinatorics, and scalable network analysis algorithms
• Experience developing software tools and AI systems for enterprise or national security applications
• Demonstrated software development skills and familiarity with modern software engineering practices (version control, CI/CD, testing)
• Expertise with deep learning frameworks such as PyTorch or TensorFlow, with proficiency in Python
• Experience with distributed computing frameworks (MPI, Horovod, Ray) and orchestration tools like Kubernetes
• Proficiency in performance-oriented languages/environments such as C++ and CUDA
• Familiarity with distributed training, hyperparameter tuning, and HPC systems
• Hands-on experience with model optimization techniques (quantization, pruning, distillation) and hardware acceleration
• Experience with MLOps toolchains for CI/CD, experiment tracking, and monitoring (e.g., MLflow, Kubeflow, TFX)
• Knowledge of human-centered AI principles and UX design for model-driven applications
• Knowledge of high-assurance and high-reliability AI, red-teaming, interpretability
• Strong collaboration skills in dynamic, interdisciplinary teams and experience mentoring junior scientists and engineers
• Experience developing and deploying large language models, multimodal AI systems, or advanced reinforcement-learning agents
• Contributions to open-source AI frameworks or peer-reviewed research publications
• Experience implementing secure AI workflows in classified or regulated environments
• Specialized expertise in network science techniques for counter-adversarial detection
• Ability to obtain and maintain a Sensitive Compartmented Information (SCI) clearance, which may require a polygraph test

Sandia's Secure Algorithms team is advancing adoption and use of AI for Laboratory mission needs. The advances are to develop and evaluate scientific AI capability itself for security and reliability, and deliver aware and resilient AI-based solutions for national security, science, and applied energy missions.

This posting will be open for application submissions for a minimum of three (3) calendar days, including the 'posting date'. Sandia reserves the right to extend the posting date at any time.

Sandia is required by DOE to conduct a pre-employment drug test and background review that includes checks of personal references, credit, law enforcement records, and employment/education verifications. Applicants for employment need to be able to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship. If you hold more than one citizenship (i.e., of the U.S. and another country), your ability to obtain a security clearance may be impacted.

Applicants offered employment with Sandia are subject to a federal background investigation to meet the requirements for access to classified information or matter if the duties of the position require a DOE security clearance. Substance abuse or illegal drug use, falsification of information, criminal activity, serious misconduct or other indicators of untrustworthiness can cause a clearance to be denied or terminated by DOE, resulting in the inability to perform the duties assigned and subsequent termination of employment.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status and any other protected class under state or federal law.

If you have a Medical Portable Electronic Device (MedPED), such as a pacemaker, defibrillator, drug-releasing pump, hearing aids, or diagnostic equipment and other equipment for measuring, monitoring, and recording body functions such as heartbeat and brain waves, if employed by Sandia National Laboratories you may be required to comply with NNSA security requirements for MedPEDs.

If you have a MedPED and you are selected for an on-site interview at Sandia National Laboratories, there may be additional steps necessary to ensure compliance with NNSA security requirements prior to the interview date.