Artificial Intelligence Integration Engineer; Scientist

Artificial Intelligence Integration Engineer (Scientist 1/2)

Apply for the Artificial Intelligence Integration Engineer (Scientist 1/2) role at Los Alamos National Laboratory
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This position will be filled at the Scientist 1 or Scientist 2 level, depending on the skills of the selected candidate. Additional responsibilities (outlined below) will be assigned if the candidate is hired at the higher level.

We are hiring a team to pioneer trustworthy and reliable artificial intelligence (AI) methods that will revolutionize scientific discovery and national security. At Los Alamos National Laboratory (LANL), the X Computational Physics Division’s Artificial Intelligence for Nuclear Deterrence Group (XCP‑AI4ND) develops, validates, and delivers machine learning systems that enhance the safety, reliability, and performance of the nation’s nuclear deterrent. Specifically, the group builds AI tools for weapons physics to support the laboratory’s mission of maintaining and modernizing the U.S. nuclear stockpile while exploring future deterrent options.

These AI tools accelerate weapons design, engineering, production, certification, and assessment processes, while also strengthening the assessment and mitigation of global security threats. As an AI Research Engineer in XCP‑AI4ND, you will lead workflow compression efforts by applying large language models and other AI techniques to streamline critical phases of the nuclear weapons lifecycle.

You will work closely with computational physicists and national security experts in the X Computational Physics (XCP) Division, leveraging some of the world’s most advanced super‑computers and global expertise in multi‑physics simulation. XCP staff span a wide range of computational physics modeling disciplines including numerical fluid and solid mechanics, materials science, radiation hydrodynamics, plasma physics, turbulence, magnetohydrodynamics, high explosives, nuclear physics and engineering, and neutral and charged particle transport.

Other research efforts focus on optimizing physics algorithms for both homogeneous and heterogeneous high‑performance computing platforms. Our scientists conduct applied physics and engineering research, implement models into production codes using strong software development practices, test and validate these methods, and assist users with adoption. At LANL, you will be part of a thriving, interdisciplinary research environment, working alongside leading scientists and engineers to tackle some of the world’s hardest science and security challenges.

We are seeking talented software engineers and scientists to join our teams located in Los Alamos, New Mexico and Ann Arbor, Michigan. Selected candidates will have the opportunity to choose their work location based on personal preference and project fit. Both locations offer unique opportunities for professional growth and impact. Please indicate your preferred work location in your cover letter when applying.

Scientist 1: $94,500 – $154,600

Scientist 2: $104,100 – $172,200

• Software Engineering:
  Front‑end or back‑end development experience, including API design, UI/UX, or scientific application support. Strong coding skills in Python, Julia, C++, and Fortran are highly desirable.
• AI Model Deployment:
  Experience deploying AI/ML models into operational or production environments, including use of high‑performance computing workflows or containerization in cloud deployments.
• AI Productivity Tools:
  Experience using AI coding assistants.
• System Administration:
  Proficiency working in Unix/Linux environments; experience managing user environments, packages, and cluster jobs or servers is highly valued.
• MLOps / Dev Ops:
  Familiarity with automated CI/CD pipelines, software versioning, model versioning, container orchestration (e.g., Kubernetes), or workflow tools.

• Experience leading technical efforts in AI deployment, software development, or Dev Ops engineering, on production‑scale projects.
• Ability to mentor junior engineers or team members on software engineering best practices.
• Demonstrated ownership of research or…