Postdoctoral Appointee - Artificial Intelligence Modeling - 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
• 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://www.sandia.gov

*These benefits vary by job classification.

Sandias artificial intelligence (AI) team is building the U.S. Department of Energys (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 Models Pillar team to architect, develop, and deploy fine-tuned reasoning models, domain foundation models, high-fidelity surrogate models, and autonomous agents. Your work will compress mission timelines by enabling scientists and engineers to explore design spaces, evaluate outcomes, and steer experiments and simulations with transparent, high-assurance AI workflows.

We anticipate multiple hires for the Models 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!

Key Responsibilities

• Research, fine-tune, and certify large reasoning models (LLMs, graph neural nets, vision transformers, etc.) for domain tasks in materials science, chemistry, physics, grid controls, and nuclear security
• Develop and integrate domain foundation models trained or adapted on DOE simulation, experimental, and production data
• Build AI surrogates to accelerate exascale multiphysics simulations, enabling millisecond-scale predictions
• Design and implement multiagent frameworks (hypothesizers, planners, executors, retrievers, assessors) with transparent decision graphs, uncertainty quantification, and audit logs
• Embed continuous learning pipelines: connect model training/evaluation to live telemetry from HPC clusters, experiments, and autonomous labs
• Develop a model repository with metadata, SBOMs, versioning, drift/poisoning surveillance, and periodic recertification
• Develop and implement high-assurance controls: least-privilege execution, runtime shields/tripwires, deterministic fallbacks, cryptographic provenance, and enclave attestation for sensitive workloads
• Collaborate with Data and Infrastructure teams to align model requirements with data lakehouses, compute fabric, and edge inference systems
• Contribute to open-source and internal AI frameworks, toolkits, and best practices for agentic workflows

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

• Prototype a custom transformer for multisensor fusion in an agile-deterrence scenario
• Optimize a surrogate neural network to replace a costly physics submodule in a reactor design simulation
• Design a Planner agent that orchestrates HPC jobs, digital-twin simulations, and robotic chemistry runs
• Run red-team evaluations to stress-test a foundation model for adversarial robustness and fairness
• Package a model into a container with Kubernetes operators for deployment in a classified enclave
• Advise domain scientists on prompt engineering and model-based hypothesis generation
• Publish and present fundamental insights to laboratory and academic audiences
• Present prototype demos and research results to stakeholders across DOE, DoD, IC, and industry

Our AI initiative is a laboratory wide effort. Candidates may be considered for placement in other organizations throughout the labs. The selected applicant can work 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.

• Possess, or are pursuing, a PhD in Computer Science, Electrical Engineering, Mathematics or a related science or engineering field, PhD must be conferred within five years prior to
• Significant research in AI, ML, data science, or a closely related field with thesis or dissertation research
• Expertise with deep learning frameworks (PyTorch, TensorFlow) and proficiency in Python
• Ability to acquire and maintain a DOE Q-level security clearance

• Strong collaboration skills in dynamic, interdisciplinary teams and experience mentoring junior engineers
  • Excellent written and verbal communication skills for both technical and non-technical audiences
  • Proven ability to work and communicate effectively in a collaborative and interdisciplinary team environment.
  • Experience and proficiency with:
• Developing and deploying large language models, multimodal AI systems, or advanced reinforcement-learning agents
• Model optimization techniques: quantization, pruning, distillation
• Hardware acceleration
• MLOps toolchains for CI/CD, experiment tracking, and monitoring: MLflow, Kubeflow, TFX
• C++, CUDA, or other performance-oriented languages/environments
• Contributing to open-source AI frameworks or publishing peer-reviewed research
• Integrating AI workflows with robotics, experimental facilities, or digital twins
• Distributed training frameworks: MPI, Horovod, Ray
• Hyperparameter tuning
• HPC systems
• Implementing secure AI workflows in classified or regulated environments
• Knowledge of human-centered AI principles and UX design for model-driven applications
• Knowledge of high-assurance AI: formal methods, red-teaming, interpretability, and runtime safety
• Ability to obtain and maintain a SCI clearance, which may require a polygraph test.

You will be part of a multi-disciplinary, success-oriented team working on mission-critical AI model development and deployment with national security implications. Occasional travel may be required. If youre passionate about advancing cutting-edge AI algorithms and building the software infrastructure that powers them, we want to hear from you!

The Center for Computing Research (CCR) at Sandia creates technology and solutions for many of our nation's most demanding national security challenges. The Center's portfolio spans the spectrum from fundamental research to state-of-the-art applications. Our work includes computer system architecture (both hardware and software); enabling technology for modeling physical and engineering systems; and research in discrete mathematics, data analytics, cognitive modeling, and decision support materials.

You will be part of a multi-disciplinary, success-oriented team working on mission-critical AI model development and deployment with national security implications. Occasional travel may be required. If youre passionate about advancing cutting-edge AI algorithms and building the software infrastructure that powers them, we want to hear from you.

This posting will be open for application submissions for a minimum of seven (7) 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.

This postdoctoral position is a temporary position for up to one year, which may be renewed at Sandia's discretion up to five additional years. The PhD must have been conferred within five years prior to employment.

Individuals in postdoctoral positions may bid on regular Sandia positions as internal candidates, and in some cases may be converted to regular career positions during their term if warranted by ongoing operational needs, continuing availability of funds, and satisfactory job performance.