Early Career Artificial Intelligence (AI) Data Science
Sandia National Laboratories, Albuquerque, NM, United States
Early Career Artificial Intelligence (AI) Data Science
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.
Benefits and Compensation
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 401(k), learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance.
Salary range: $102,400 – $199,700. 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.
What Your Job Will Be Like
Sandia’s artificial intelligence (AI) team is building the U.S. Department of Energy’s (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. You will join the Data Pillar team to design, implement, and operate Sandia’s AI‑ready, zero‑trust data ecosystem. Your work will transform raw simulation outputs, sensor and facility logs, experimental records, and production data into governed, provenance‑tracked, and access‑controlled datasets that power AI models, autonomous agents, and mission workflows across DOE’s HPC, cloud, and edge environments.
Key Responsibilities
AI Solution Development & Deployment
Design, prototype, and deploy AI‑driven applications that solve real organizational challenges.
Integrate large language models (LLMs), computer vision, and other AI capabilities into production environments.
Build and maintain APIs, pipelines, and interfaces that connect AI models to enterprise systems.
R&D Translation
Evaluate emerging AI tools, frameworks, and research from academia and industry.
Rapidly prototype promising technologies to assess feasibility and value.
Operationalize proven concepts into robust, user‑friendly systems.
Workflow & Automation Engineering
Build intelligent workflows that automate data processing, analysis, and decision support.
Leverage orchestration tools and MLOps practices for reliable AI lifecycle management.
Design systems that integrate human feedback and oversight where needed.
Partner with data stewards to ensure clean, context‑rich data fuels AI solutions.
Collaborate with domain experts to define use cases and success metrics.
Provide guidance and templates that help other teams safely and effectively adopt AI tools.
Quality, Ethics, and Governance
Implement responsible AI principles, including bias testing, explainability, and auditability.
Document model assumptions, limitations, and operational dependencies.
Ensure compliance with data protection and organizational security policies.
Daily Activities
Prototype new AI workflows using frameworks like LangChain, Hugging Face, or OpenAI APIs.
Connect AI systems to enterprise data sources, dashboards, and collaboration tools.
Work with MLOps pipelines (e.g., MLflow, Kubeflow, or Vertex AI) for deployment and monitoring.
Evaluate new open‑source models or vendor tools and test their performance on internal data.
Collaborate with IT and cybersecurity teams to deploy AI tools securely.
Collaborate on public‑private partnerships and multi‑lab federated data efforts.
Create documentation, tutorials, and reusable components to scale adoption.
Meet with mission or program teams to identify where AI can streamline workflow.
About Our Team
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.
Qualifications We Require
A Bachelor’s degree in a relevant STEM discipline such as Data Science, Statistics, or an equivalent combination of directly relevant education and engineering or scientific experience that demonstrates the knowledge, skills, and ability to perform independent research and development.
Ability to acquire and maintain a DOE Q clearance.
Qualifications We Desire
Graduate degree (M.S. or Ph.D.) in a relevant computationally‑intensive discipline with an independent research project requirement (e.g., thesis or dissertation).
Experience in developing software for enterprise and national security applications.
Experience acquiring, preparing, and analyzing real‑world data.
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.
Degree in Data Science, Informatics, Statistics, or a related STEM field with a significant data research component.
Background in AI‑mediated data curation: automated annotation, feature extraction, and dataset certification.
Familiarity with data security and zero‑trust principles, including secure enclaves, attribute‑based access control, and data masking or differential privacy.
Familiarity with FAIR (Findable, Accessible, Interoperable, Reusable) data practices.
Experience implementing data governance and metadata management tools (e.g., Apache Atlas, DataHub, Collibra).
Experience with programming languages such as Python, R, SQL.
Working knowledge of a variety of machine learning concepts, techniques, models, and tools.
Familiarity with agile principles and practices.
Implementing data policies for classified, export‑controlled, or proprietary data.
Advanced and automated data wrangling techniques for raw heterogeneous and streaming data sources, particularly for AI input.
Ability to obtain and maintain an SCI clearance, which may require a polygraph test.
Security Clearance
Candidates must obtain and maintain a DOE Q‑level security clearance, which requires U.S. citizenship.
EEO
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, 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, and you are 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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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.
Benefits and Compensation
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 401(k), learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance.
Salary range: $102,400 – $199,700. 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.
What Your Job Will Be Like
Sandia’s artificial intelligence (AI) team is building the U.S. Department of Energy’s (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. You will join the Data Pillar team to design, implement, and operate Sandia’s AI‑ready, zero‑trust data ecosystem. Your work will transform raw simulation outputs, sensor and facility logs, experimental records, and production data into governed, provenance‑tracked, and access‑controlled datasets that power AI models, autonomous agents, and mission workflows across DOE’s HPC, cloud, and edge environments.
Key Responsibilities
AI Solution Development & Deployment
Design, prototype, and deploy AI‑driven applications that solve real organizational challenges.
Integrate large language models (LLMs), computer vision, and other AI capabilities into production environments.
Build and maintain APIs, pipelines, and interfaces that connect AI models to enterprise systems.
R&D Translation
Evaluate emerging AI tools, frameworks, and research from academia and industry.
Rapidly prototype promising technologies to assess feasibility and value.
Operationalize proven concepts into robust, user‑friendly systems.
Workflow & Automation Engineering
Build intelligent workflows that automate data processing, analysis, and decision support.
Leverage orchestration tools and MLOps practices for reliable AI lifecycle management.
Design systems that integrate human feedback and oversight where needed.
Partner with data stewards to ensure clean, context‑rich data fuels AI solutions.
Collaborate with domain experts to define use cases and success metrics.
Provide guidance and templates that help other teams safely and effectively adopt AI tools.
Quality, Ethics, and Governance
Implement responsible AI principles, including bias testing, explainability, and auditability.
Document model assumptions, limitations, and operational dependencies.
Ensure compliance with data protection and organizational security policies.
Daily Activities
Prototype new AI workflows using frameworks like LangChain, Hugging Face, or OpenAI APIs.
Connect AI systems to enterprise data sources, dashboards, and collaboration tools.
Work with MLOps pipelines (e.g., MLflow, Kubeflow, or Vertex AI) for deployment and monitoring.
Evaluate new open‑source models or vendor tools and test their performance on internal data.
Collaborate with IT and cybersecurity teams to deploy AI tools securely.
Collaborate on public‑private partnerships and multi‑lab federated data efforts.
Create documentation, tutorials, and reusable components to scale adoption.
Meet with mission or program teams to identify where AI can streamline workflow.
About Our Team
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.
Qualifications We Require
A Bachelor’s degree in a relevant STEM discipline such as Data Science, Statistics, or an equivalent combination of directly relevant education and engineering or scientific experience that demonstrates the knowledge, skills, and ability to perform independent research and development.
Ability to acquire and maintain a DOE Q clearance.
Qualifications We Desire
Graduate degree (M.S. or Ph.D.) in a relevant computationally‑intensive discipline with an independent research project requirement (e.g., thesis or dissertation).
Experience in developing software for enterprise and national security applications.
Experience acquiring, preparing, and analyzing real‑world data.
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.
Degree in Data Science, Informatics, Statistics, or a related STEM field with a significant data research component.
Background in AI‑mediated data curation: automated annotation, feature extraction, and dataset certification.
Familiarity with data security and zero‑trust principles, including secure enclaves, attribute‑based access control, and data masking or differential privacy.
Familiarity with FAIR (Findable, Accessible, Interoperable, Reusable) data practices.
Experience implementing data governance and metadata management tools (e.g., Apache Atlas, DataHub, Collibra).
Experience with programming languages such as Python, R, SQL.
Working knowledge of a variety of machine learning concepts, techniques, models, and tools.
Familiarity with agile principles and practices.
Implementing data policies for classified, export‑controlled, or proprietary data.
Advanced and automated data wrangling techniques for raw heterogeneous and streaming data sources, particularly for AI input.
Ability to obtain and maintain an SCI clearance, which may require a polygraph test.
Security Clearance
Candidates must obtain and maintain a DOE Q‑level security clearance, which requires U.S. citizenship.
EEO
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, 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, and you are 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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