Sandia National Laboratories
Postdoctoral Appointee - Artificial Intelligence Data Science - Hybrid
Sandia National Laboratories, Livermore, California, United States, 94551
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.
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*
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 Sandia's AI team 1466 is building DOE's next‑generation AI Platform around three pillars Data, Models, and Infrastructure to solve high‑impact "lighthouse problems" in agile deterrence, energy dominance, and critical minerals. As a Postdoctoral Appointee, you’ll 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
Build and operate an AI‑Ready Lakehouse
Design and maintain a federated data lakehouse with full provenance/versioning, attribute‑based access control, license/consent automation, and agent telemetry services
Implement automated, AI‑mediated ingestion pipelines for heterogeneous sources (HPC simulation outputs, experimental instruments, robotics, sensor streams, satellite imagery, production logs)
Enforce Data Security & Assurance
Develop a Data Health & Threat program: dataset fingerprinting, watermarking, poisoning/anomaly detection, red‑team sampling, and reproducible training manifests
Configure secure enclaves and egress processes for CUI, Restricted Data, and other sensitive corpora with attestation and differential‑privacy where required
Define and Implement Data Governance
Establish FAIR‑compliant metadata standards, data catalogs, and controlled‑vocabulary ontologies
Automate lineage tracking, quality checks, schema validation, and leak controls at record‑level granularity
Instrument AI Workflows with Standardized Telemetry
Deploy Agent Trace Schema (ATS) and Agent Run Record (ARR) frameworks to log tool calls, decision graphs, human hand‑offs, and environment observations
Treat agent‑generated artifacts (plans, memory, configurations) as first‑class data objects
Collaborate Across Pillars
Work with Models and Interfaces teams to integrate data services into training, evaluation, and inference pipelines
Partner with Infrastructure engineers to optimize data movement, tiered storage, and high‑bandwidth networking (ESnet) between HPC, cloud, and edge
Engage domain scientists and mission leads for agile deterrence, energy grid, and critical minerals use cases to curate problem‑specific datasets
Support Continuous Acquisition & Benchmarking
Design edge‑to‑exascale data acquisition systems with robotics and instrument integration
Develop data/AI benchmarksdatasets, tools, and metricsfor pipeline performance, model evaluation, and mission KPIs
On Any Given Day, You May Be Called Upon To
Author an AI‑mediated parser for a new experimental instrument, automatically extracting and cataloging metadata
Implement an attribute‑based policy that blocks unapproved data combinations in a classified enclave
Prototype a streaming pipeline that feeds live sensor data from a nuclear facility into an HPC training queue
Develop a dashboard that alerts on data drift, pipeline failures, or anomalous records
Collaborate with MLOps engineers to version datasets alongside model artifacts in CI/CD
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.
Our AI initiative is a laboratory‑wide effort. Candidates may be considered for placement in other organizations throughout the labs.
Qualifications We Require
Possess, or are pursuing, a PhD in Computer Science, Data Science, Statistics, or a related science or engineering field; PhD must be conferred within five years prior to employment
Experience or knowledge in these areas:
Building and maintaining production data pipelines (ETL/ELT) and data warehouses or data lakes
Programming languages such as Python, SQL, and experience with frameworks like Apache Spark or Dask
Data security and zero‑trust principles, including secure enclaves, attribute‑based access control, and data masking or differential privacy
Cloud platforms (AWS, Azure, or GCP) and container orchestration (Kubernetes)
Ability to acquire and maintain a DOE Q‑level security clearance
Qualifications We Desire
Significant data research experience
Background in AI‑mediated data curation: automated annotation, feature extraction, and dataset certification
Experience implementing data governance and metadata management tools (e.g., Apache Atlas, DataHub, Collibra)
Experience developing and refining data architectures and data flows
Hands‑on background in MLOps and CI/CD for data and ML workflows (e.g., Jenkins, GitLab CI, MLflow)
Knowledge of human‑factors engineering and UX design principles for data platforms
Knowledge of agile principles and practices and experience working as part of agile teams
Ability to work effectively in a dynamic, interdisciplinary environment, guiding technical decisions and mentoring junior staff
Strong written and verbal communication skills, with the ability to present complex data concepts to diverse audiences
Ability to obtain and maintain a SCI clearance, which may require a polygraph test
Also, for this posting we are seeking individuals with the following experience:
Curating and managing scientific or engineering datasets
Designing and enforcing data policies for classified, export‑controlled, or proprietary data
Data architecture for HPC and edge‑computing environments
Advanced data "munging" fusion techniques for heterogeneous and streaming data sources
Building data pipelines for feature stores, experiment tracking, and model drift monitoring
Designing and enforcing data policies for classified, export‑controlled, or proprietary data
Collaborating on public‑private partnerships or multi‑lab federated data efforts
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.
You will be part of a multi‑disciplinary, mission‑focused team delivering foundational data capabilities for transformative AI systems in national security, energy, and critical materials. Occasional travel may be required. If you’re passionate about building the data backbone for next‑generation AI at scale, we want to hear from you.
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, 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.
Position Information 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.
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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*
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 Sandia's AI team 1466 is building DOE's next‑generation AI Platform around three pillars Data, Models, and Infrastructure to solve high‑impact "lighthouse problems" in agile deterrence, energy dominance, and critical minerals. As a Postdoctoral Appointee, you’ll 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
Build and operate an AI‑Ready Lakehouse
Design and maintain a federated data lakehouse with full provenance/versioning, attribute‑based access control, license/consent automation, and agent telemetry services
Implement automated, AI‑mediated ingestion pipelines for heterogeneous sources (HPC simulation outputs, experimental instruments, robotics, sensor streams, satellite imagery, production logs)
Enforce Data Security & Assurance
Develop a Data Health & Threat program: dataset fingerprinting, watermarking, poisoning/anomaly detection, red‑team sampling, and reproducible training manifests
Configure secure enclaves and egress processes for CUI, Restricted Data, and other sensitive corpora with attestation and differential‑privacy where required
Define and Implement Data Governance
Establish FAIR‑compliant metadata standards, data catalogs, and controlled‑vocabulary ontologies
Automate lineage tracking, quality checks, schema validation, and leak controls at record‑level granularity
Instrument AI Workflows with Standardized Telemetry
Deploy Agent Trace Schema (ATS) and Agent Run Record (ARR) frameworks to log tool calls, decision graphs, human hand‑offs, and environment observations
Treat agent‑generated artifacts (plans, memory, configurations) as first‑class data objects
Collaborate Across Pillars
Work with Models and Interfaces teams to integrate data services into training, evaluation, and inference pipelines
Partner with Infrastructure engineers to optimize data movement, tiered storage, and high‑bandwidth networking (ESnet) between HPC, cloud, and edge
Engage domain scientists and mission leads for agile deterrence, energy grid, and critical minerals use cases to curate problem‑specific datasets
Support Continuous Acquisition & Benchmarking
Design edge‑to‑exascale data acquisition systems with robotics and instrument integration
Develop data/AI benchmarksdatasets, tools, and metricsfor pipeline performance, model evaluation, and mission KPIs
On Any Given Day, You May Be Called Upon To
Author an AI‑mediated parser for a new experimental instrument, automatically extracting and cataloging metadata
Implement an attribute‑based policy that blocks unapproved data combinations in a classified enclave
Prototype a streaming pipeline that feeds live sensor data from a nuclear facility into an HPC training queue
Develop a dashboard that alerts on data drift, pipeline failures, or anomalous records
Collaborate with MLOps engineers to version datasets alongside model artifacts in CI/CD
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.
Our AI initiative is a laboratory‑wide effort. Candidates may be considered for placement in other organizations throughout the labs.
Qualifications We Require
Possess, or are pursuing, a PhD in Computer Science, Data Science, Statistics, or a related science or engineering field; PhD must be conferred within five years prior to employment
Experience or knowledge in these areas:
Building and maintaining production data pipelines (ETL/ELT) and data warehouses or data lakes
Programming languages such as Python, SQL, and experience with frameworks like Apache Spark or Dask
Data security and zero‑trust principles, including secure enclaves, attribute‑based access control, and data masking or differential privacy
Cloud platforms (AWS, Azure, or GCP) and container orchestration (Kubernetes)
Ability to acquire and maintain a DOE Q‑level security clearance
Qualifications We Desire
Significant data research experience
Background in AI‑mediated data curation: automated annotation, feature extraction, and dataset certification
Experience implementing data governance and metadata management tools (e.g., Apache Atlas, DataHub, Collibra)
Experience developing and refining data architectures and data flows
Hands‑on background in MLOps and CI/CD for data and ML workflows (e.g., Jenkins, GitLab CI, MLflow)
Knowledge of human‑factors engineering and UX design principles for data platforms
Knowledge of agile principles and practices and experience working as part of agile teams
Ability to work effectively in a dynamic, interdisciplinary environment, guiding technical decisions and mentoring junior staff
Strong written and verbal communication skills, with the ability to present complex data concepts to diverse audiences
Ability to obtain and maintain a SCI clearance, which may require a polygraph test
Also, for this posting we are seeking individuals with the following experience:
Curating and managing scientific or engineering datasets
Designing and enforcing data policies for classified, export‑controlled, or proprietary data
Data architecture for HPC and edge‑computing environments
Advanced data "munging" fusion techniques for heterogeneous and streaming data sources
Building data pipelines for feature stores, experiment tracking, and model drift monitoring
Designing and enforcing data policies for classified, export‑controlled, or proprietary data
Collaborating on public‑private partnerships or multi‑lab federated data efforts
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.
You will be part of a multi‑disciplinary, mission‑focused team delivering foundational data capabilities for transformative AI systems in national security, energy, and critical materials. Occasional travel may be required. If you’re passionate about building the data backbone for next‑generation AI at scale, we want to hear from you.
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, 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.
Position Information 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.
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