Data Scientist II - AI Assurance Researcher

Overview

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget.

Our Science & Technology directorates include National Security, Integrated Discovery Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus.

The National Security Directorate (NSD) drives science-based, mission-focused solutions to take on complex, real-world threats to our nation and the world.

The AI and Data Analytics Division, part of the National Security Directorate, combines profound domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytic challenges. Working in multidisciplinary teams, we connect foundational research to engineering to operations, providing the tools to innovate quickly and field results faster. Our strengths are integrated across the data analytics lifecycle, from data acquisition and management to analysis and decision support.

Rockstar Rewards

Employees and their families are offered medical insurance, dental insurance, vision insurance, robust telehealth care options, several mental health benefits, free wellness coaching, health savings account, flexible spending accounts, basic life insurance, disability insurance\, employee assistance program, business travel insurance, tuition assistance, relocation, backup childcare, legal benefits, supplemental parental bonding leave, surrogacy and adoption assistance, and fertility support. Employees are automatically enrolled in our company-funded pension plan\ and may enroll in our 401 (k) savings plan with company match*. Employees may accrue up to 120 vacation hours per year and may receive ten paid holidays per year.

• Research Associates excluded.

All benefits are dependent upon eligibility.

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Responsibilities

PNNL is seeking a Data Scientist II - AI Assurance Researcher who has experience in understanding, exploring, and manipulating the internal mechanics and behaviors of AI models and can provide valuable insights into the decision boundaries and mathematical fingerprints of data properties. The selected candidate should have extensive experience training models, accessing and working with data embeddings, the ability to derive theoretical queries from empirical results, and demonstrate the capacity to translate research papers and findings into mission relevant insights and tools.

Key

Responsibilities

• 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.

Qualifications

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 in 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.

Hazardous Working Conditions/Environment

Not applicable.

Additional Information

This position requires the ability to obtain and maintain a federal security clearance.

A security clearance background investigation includes review of your employment, education, financial, and criminal history, as well as interviews with you and your personal references, neighbors, and co-workers to determine trustworthiness, reliability, and loyalty to the United States. The investigation also examines your foreign connections, drug and alcohol use, foreign influence, and overall conduct.

Requirements

• U.S. Citizenship
• Background Investigation: 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.
• Drug Testing: All Security Clearance positions are Testing Designated Positions, which means that the applicant selected for hire is subject to pre-employment drug testing, and post-employment random drug testing. In addition, applicants must be able to demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the requisite Questionnaire for National Security Positions (QNSP).

Note: Applicants will be consider