Sandia National Laboratories · 5 hours ago
Senior/Principal Artificial Intelligence Models, NM/CA - Hybrid
Albuquerque, NM
Full-time
Hybrid
Senior Level, Lead/Staff
$114K/yr - $228K/yr
5+ years expSandia National Laboratories is the nation’s premier science and engineering lab for national security and technology innovation. They are seeking a Senior/Principal Artificial Intelligence Models professional to join their AI team, focusing on building next-generation AI capabilities for national security and applied energy missions.
GovernmentInformation TechnologyNational Security
No H1B
Security Clearance RequiredU.S. Citizen Only
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 multi-agent 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
Establish a model repository with metadata, SBOMs, versioning, drift/poisoning surveillance, and periodic recertification
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
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
Present prototype demos and research results to stakeholders across DOE, DoD, IC, and industry
Qualification
Required
Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, 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
Preferred
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
Demonstrated expertise with deep learning frameworks (PyTorch, TensorFlow) and proficiency in Python
Experience with distributed computing frameworks (MPI, Horovod, Ray) and orchestration tools (Kubernetes)
Proficiency with C++, CUDA, or other performance-oriented languages/environments
Familiarity with distributed training frameworks (MPI, Horovod, Ray), hyperparameter tuning, and HPC systems
Hands-on experience with model optimization techniques (quantization, pruning, distillation) and hardware acceleration
Proficiency with MLOps toolchains for CI/CD, experiment tracking, and monitoring (MLflow, Kubeflow, TFX)
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
Strong collaboration skills in dynamic, interdisciplinary teams and experience mentoring junior engineers
Developing and deploying large language models, multimodal AI systems, or advanced reinforcement-learning agents
Integrating AI workflows with robotics, experimental facilities, or digital twins
Contributing to open-source AI frameworks or publishing peer-reviewed research
Implementing secure AI workflows in classified or regulated environments
Ability to obtain and maintain a SCI clearance, which may require a polygraph test
Benefits
Generous vacation
Strong medical and other benefits
Competitive 401k
Learning opportunities
Relocation assistance
Amenities aimed at creating a solid work/life balance
Company
Sandia National Laboratories
Sandia is a conducts research and development into the non-nuclear components of nuclear weapons.
10001+ employees
Funding
Current Stage
Late StageTotal Funding
$4.4MKey Investors
US Department of EnergyARPA-E
2023-09-21Grant· $0.5M
2023-07-27Grant
2023-01-10Grant· $3.7M
Leadership Team
Laura McGill
Deputy Laboratories Director - Nuclear Deterrence, and Chief Technology Officer
Maria Gallardo
CFO Enterprise Risk Management Program Lead
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