Senior Data Scientist III- AI Assurance Researcher

Pacific Northwest National Laboratory•Richland, WA

7h•$140,200 - $228,800•Onsite

About The Position

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, Earth and Biological Sciences, Physical and Computational 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 NSD, 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. PNNL is seeking a Senior Data Scientist - AI Assurance Researcher who has experience in understanding, exploring, and manipulating the internal mechanics and behaviors of AI models can provides 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.

Requirements

BS/BA and 5+ years of relevant work experience -OR- MS/MA and 3+ years of relevant work experience -OR- PhD with 1+ year of relevant experience
U.S. Citizenship
Ability to obtain and maintain a federal security clearance.
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).
Applicants will be considered ineligible for security clearance processing by the U.S. Department of Energy if non-use of illegal drugs, including marijuana, for 12 months cannot be demonstrated.
The candidate selected for this position will be subject to pre-employment and random drug testing for illegal drugs, including marijuana, consistent with the Controlled Substances Act and the PNNL Workplace Substance Abuse Program.
Must pass a drug test prior to commencing employment.
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).
Must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication.
All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation).
Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment.
Mandatory Requirements: DOE prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle.

Nice To Haves

Advanced degree in computer science, engineering, mathematics, or a related field.
Deep familiarity with the current ML research landscape, particularly in explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
Track record of peer-reviewed publications or technical contributions in relevant research areas.
Hands-on experience analyzing the internal structures and representations of deep learning models, particularly large language models and large vision models.
Strong proficiency in PyTorch and associated deep learning libraries.
Experience designing and executing large-scale experiments on HPC systems.
Demonstrated ability to translate research prototypes into deployable tools and capabilities.
Excellent communication skills, with the ability to convey complex research findings to both technical and non-technical audiences.

Responsibilities

Defines and leads research agendas in areas such as explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
Designs and executes rigorous ML experiments at scale, including large-scale training and evaluation on HPC infrastructure.
Develops novel evaluation methodologies that go beyond standard performance metrics to assess 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.
Interprets empirical results to identify promising research directions and guide strategic investment of team resources.
Establishes best practices for research code quality, reproducibility, and integration into operational pipelines.
Mentors junior researchers and engineers, fostering a culture of scientific rigor and collaborative inquiry.
Conducts work in secure environments with adherence to operational security requirements.