What Your Job Will Be Like

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-teaming, explainability, and UQ methods.
• Integrate AI/ML and ModSim 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, cloud, and emerging architectures.
• Collaborate across interdisciplinary teams both internal and external to Sandia. Communicate technical results to diverse audiences through demos, tutorials, reports, and peer-reviewed publications.
• Advise domain scientists and engineers on selection and effective use of AI and computational modeling technologies. Mentor emerging researchers as they grow into the field.

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

Salary Range

$165,000 - $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.

Qualifications We Require

• Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Artificial Intelligence, Data Science, or a related STEM field plus five (5) years of directly relevant experience, or an equivalent combination of education and experience
• Ability to obtain and maintain a DOE Q clearance

Qualifications We Desire

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:

• Advanced AI/ML expertise for scientific, security, and engineering applications, including deep learning, artificial intelligence, and general data science methods applied to complex real-world domains.
• Strong graduate research credentials with an extensive record of innovative, collaborative research and dissemination via peer-reviewed publications and/or impactful open-source contributions.
• Deep learning engineering proficiency, including Python and modern frameworks (e.g., PyTorch/TensorFlow) and experience developing LLMs, multimodal models, and/or reinforcement-learning agents.
• Scalable algorithms and mathematics strength, including mathematical modeling, reduced-order/surrogate modeling, and graph theory/network science/combinatorics.
• High-performance and parallel computing experience on large clusters and cloud platforms, including performance-oriented development (e.g., C++/CUDA) and distributed execution patterns.
• Distributed model training, tuning/optimization, acceleration/scalability and experimentation expertise.
• Modern software engineering and MLOps practices, including CI/CD, testing, version control, experiment tracking, monitoring, orchestration/deployment, and reproducible model lifecycle management.
• High-assurance, secure, and reliable AI experience, including interpretability, red-teaming/adversarial robustness, runtime safety concepts, and operating in regulated/controlled environments.
• Integration of AI into end-to-end workflows, e.g., coupling models with digital twins, robotics, experiments, or operations.
• Human-centered AI awareness, including usability/UX considerations for model-driven tools and decision-support systems.
• Leadership, communication, and teamwork, including mentoring, cross-disciplinary collaboration, and research community service/leadership.
• Ability to obtain and maintain a SCI clearance, which may require a polygraph test.

About Our Team

The Computational Data Science department researches, develops, and applies algorithms at the nexus of machine learning and computational science and engineering models. Team members develop foundational theory, algorithms, and tools, and partner to enable data-guided decision support for science and engineering mission applications. The department emphasizes fundamental, open research in new methods, notably Bayesian inference, machine learning, and reduced-order modeling. The department contributes primarily to nuclear deterrence (including the Advanced Simulation and Computing program), non-proliferation, and open research (funded largely by LDRD and DOE Office of Science).

Posting Duration

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.