Data Scientist II - AI Assurance Researcher

Overview

PNNL, a world‑class research institution, is organizationally divided into directorates encompassing specialized scientific domains such as National Security, Earth and Biological Sciences, Physical and Computational Sciences, and Energy and Environment. The National Security Directorate (NSD) drives science‑based, mission‑focused solutions to complex, real‑world threats. The AI and Data Analytics Division within the NSD combines domain expertise with advanced hardware and software to deliver computational solutions that address data and analytics challenges across the data analytics lifecycle—from acquisition to decision support.

PNNL is seeking a Data Scientist II – AI Assurance Researcher who can understand, explore, and manipulate the internal mechanics and behaviors of AI models to provide valuable insights into decision boundaries and mathematical fingerprints of data properties. The selected candidate should have extensive experience training models, working with data embeddings, deriving theoretical queries from empirical results, and translating research findings into mission‑relevant insights and tools.

• Designs and executes rigorous ML experiments following community best practices, including large‑scale training and evaluation on HPC infrastructure.
• Evaluates AI systems across multiple dimensions, including standard performance metrics, generalization, robustness, and out‑of‑distribution behavior.
• Analyzes the internal structures and representations of deep learning models, with emphasis on large language models and large vision models.
• Assesses empirical results to identify trends, inform research direction, and recommend next steps.
• Writes high‑quality, well‑documented research code that supports reproducibility and collaboration.
• Contributes to publications and technical reports that communicate findings to both internal and external audiences.
• Collaborates with senior researchers, engineers, and cross‑functional teams to integrate research into broader systems and workflows.
• Conducts work in secure environments with adherence to operational security requirements.

This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

Minimum Qualifications:

• BS/BA and 2 years of relevant experience — OR MS/MA — OR PhD

Preferred Qualifications:

• Degree in computer science, engineering, mathematics, or a related field.
• Familiarity with the current ML research landscape, particularly in explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
• Hands‑on experience analyzing the internal structures of deep learning models, particularly large language models and large vision models.
• Proficiency in PyTorch and associated deep learning libraries.
• Experience designing and executing experiments on HPC systems.
• Experience translating research prototypes into deployable tools and capabilities.
• Demonstrated strong communication and collaboration skills, with the ability to work effectively in a multi‑disciplinary team environment.

Not applicable.

This position requires the ability to obtain and maintain a federal security clearance. A security clearance background investigation includes a review of employment, education, financial, and criminal history, as well as interviews with references, neighbors, and co‑workers to determine trustworthiness, reliability, and loyalty to the United States. The investigation examines foreign connections, drug and alcohol use, foreign influence, and overall conduct.

Applicants selected will be subject to a federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10

CFR
710, Appendix

B. All security‑clearance positions are testing designated positions and are subject to pre‑employment and random drug testing for illegal drugs, including marijuana, in compliance with the Controlled Substances Act and the PNNL Workplace Substance Abuse Program.

• U.S. Citizenship
• Background investigation per DOE 10
  
  CFR
  710, AppendixB
• Drug testing: pre‑employment and random…