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Postdoctoral Appointee- Machine Learning and Artificial Intelligence

Postdoctoral Appointee- Machine Learning and Artificial Intelligence

Sandia National LaboratoriesAlbuquerque, NM, United States
8 days ago
Job type
  • Full-time
  • Part-time
Job description

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Job ID

696331

Location

Albuquerque, NM

Full / Part Time

Full-Time

Regular / Temporary

Temporary

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About Sandia

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.
  • What Your Job Will Be Like

    We are seeking a Postdoctoral Appointee in Machine Learning and Artificial Intelligence to research, design, and deploy next-generation agentic frameworks to accelerate scientific discovery, engineering design and advanced manufacturing and qualification strategies. The successful candidate will develop and deploy novel ML / AI architectures including generative, multi-agent, and simulation-informed models that can reason, plan, and collaborate in scientific contexts.

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

  • Collaborate with domain experts across physics, manufacturing, and computational modeling to integrate AI solutions into complex simulation and scientific workflows.
  • Contribute to codebases that implement modular, containerized (e.g., Docker / Singularity) ML solutions for distributed computing environments.
  • Prototype AI frameworks that integrate simulation, optimization, and ML-driven reasoning for scientific or engineering workflows.
  • Develop and deploy machine learning pipelines in Python using frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.
  • Integrate state of the art and open source generative AI models into broader AI-enabled workflows
  • Design, train, and evaluate large-scale generative models or agentic architectures for scientific data synthesis and design tasks.
  • Assist in defining and refining research vision, roadmaps, and success criteria for AI-enabled multi-agent frameworks.
  • Conduct and publish novel research in generative AI, autonomous agents, or AI-driven design acceleration.
  • Present results through internal reports, external publications, and conferences.
  • Mentor interns or junior researchers in applied AI development.
  • Due to the nature of the work, the selected applicant must be able to work onsite at least 75% of the time.

    Qualifications We Require

  • Ph.D. (earned within the past 5 years, or anticipated within 6 months) in Computer Science, Applied Mathematics, Mechanical Engineering, or related STEM discipline
  • Ability to obtain and maintain DOE Q-level security clearance
  • Experience developing and deploying AI agents, multi-agent frameworks, or LLM-based tool use systems
  • Proficiency in Python and experience with at least one major ML framework (e.g., PyTorch, TensorFlow, JAX, Hugging Face Transformers)
  • Working understanding of generative AI methods such as diffusion models, LLMs, or VAEs
  • Strong analytical, written, and verbal communication skills
  • Ability to work collaboratively in multi-disciplinary research environments
  • Qualifications We Desire

  • Demonstrated research experience in machine learning, deep learning, or artificial intelligence (e.g., publications, code repositories, or preprints)
  • Experience with containerized workflows (Docker, Singularity) and software versioning (Git, GitHub / GitLab CI / CD)
  • Exposure to modeling and simulation tools, scientific computing, or digital twin frameworks
  • Familiarity with reinforcement learning, autonomous experimentation, or AI-for-science use cases
  • Demonstrated ability to integrate ML with physics-informed or hybrid modeling approaches
  • Experience with high-performance computing (HPC) or cloud-based ML development (e.g., Slurm, Kubernetes, AWS / GCP)
  • Evidence of leadership potential through mentoring, collaboration, or open-source contributions
  • About Our Team

    The Advanced Metal Processing Department and Rapid Development Machine Shop provides scientific and engineering expertise in the areas of advanced manufacturing, metal additive manufacturing and laser machining / surface modification. Advanced manufacturing includes the design and fabrication of components by conventional subtractive machining, additive manufacturing, electrical discharge machining (EDM), laser machining, laser etching / annealing, vacuum induction melting, and optical probe measurements. Metal additive manufacturing expertise includes alloy development, qualification / acceptance, and design. Current technologies utilized include laser powder bed, metal fused deposition (FDM), and powder and wire directed energy deposition (DED). Our staff supports a variety of programs and is highly engaged in providing collaborative, innovative materials science and systems-based engineering solutions.The analytic capabilities available : High Speed Microscopy, High Speed Thermal Imaging, Thermal Desorption, Thermal Diffusivity, Particle Size Analysis, Avalanche Angle Measurement, Thermal Imaging, plus others.

    Posting Duration

    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.

    Security Clearance

    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.

    EEO

    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.

    NNSA Requirements for MedPEDs

    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.

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    And Machine Learning • Albuquerque, NM, United States

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