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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist III - AI Assurance Researcher - **Company:** Pacific Northwest National Laboratory - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $140,200 - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Computer Vision, Python (Programming Language), Machine Learning, Pytorch, Deep Learning - **Published:** November 14, 2026 - **Apply:** https://www.seattlejobs.com/job.asp?id=3512893267&tx=KR9191FFR&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * BS/BA and 5+ years of data science experience -OR- * MS/MA and 3+ years of data science experience -OR- * PhD with 1+ year of data science experience * Experience conducting deep learning research to investigate how models learn, behave, or generalize. * Experience using Python and PyTorch for deep learning research., * Experience explaining model behavior through analysis of internal representations and computations, including mechanistic interpretability of large language or vision models. * Experience developing or evaluating methods to assess tool-using models and multi-step agentic workflows, including analysis of execution traces, task outcomes, and failure modes. * Experience designing and executing large-scale deep learning experiments. * Experience leading research projects or major technical efforts, including formulating research questions, developing or adapting methods, coordinating contributors, and evaluating and communicating results. * Experience translating research prototypes into tools or capabilities or contributing peer-reviewed publications or other technical contributions in relevant research areas. * Experience supporting national security missions. 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., * 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 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. ## Description PNNL is seeking a deep learning researcher to investigate how AI models learn and make decisions, and to develop methods for assessing and improving their reliability. You will connect internal representations and computations to observable behavior, using those findings to explain model decisions and examine how uncertainty, changing conditions, or adversarial inputs affect the reliability of model outputs. At PNNL, your research will address national security and safety needs. You will have opportunities to collaborate across the U.S. government and develop and pursue new research ideas that advance AI Assurance and address mission needs. You will lead research projects or major parts of larger efforts, develop research questions and methods, and mentor colleagues while remaining hands-on in experimental research. Relevant experience may include research on deep learning fundamentals, such as optimization, representations, or generalization., * Lead research projects or major parts of larger efforts, coordinating the technical approach, team contributions, and research milestones. * Formulate research questions, develop or adapt methods, and design and execute deep learning experiments, including large-scale experiments on high-performance computing (HPC) infrastructure as appropriate. * Investigate how model architectures, training dynamics, and internal computations shape behavior, using findings from systems such as large language and vision models to explain observed capabilities and failure modes. * Develop methods to quantify uncertainty and assess robustness under distribution shifts or adversarial inputs, using red and blue teaming to identify vulnerabilities and evaluate defensive methods. * Develop reproducible evaluations to investigate model reliability and failure modes, compare methods against appropriate baselines, and communicate findings, uncertainty, and limitations. * Develop reproducible research code and collaborate with engineers to translate findings and prototypes into useful tools and capabilities. * Lead the preparation of publications, technical reports, and presentations that communicate the team's findings. * Mentor researchers and engineers through technical discussions, feedback, and collaborative research. * Develop research ideas and contribute to proposals with collaborators. * Conduct work in secure environments in accordance with operational security requirements.