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Pacific Northwest National Laboratory

National lab advancing energy, security, environment

Senior Data Scientist/PI - Evaluating Foundation Models and SI Agents for National Security

Natural Language Processing & LLMsUpdated on Nov 13
Full-time$140.2k - $228.8k /yr

About the Job

Requirements

  • A Bachelor of Science or Bachelor of Arts degree and at least 5 years of data science experience, or a Master of Science or Master of Arts degree and at least 3 years of data science experience, or a PhD and at least 1 year of data science experience.
  • Experience setting technical direction and leading technical work on research projects.
  • U.S. citizenship is required.
  • Must meet eligibility requirements for access to classified matter under 10 CFR 710, Appendix B, and pass a federal background investigation.
  • Must demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the Questionnaire for National Security Positions; security-clearance positions are subject to pre-employment and random drug testing.
  • Must obtain and maintain the required federal security clearance and the HSPD-12 Personal Identity Verification credential, with a favorable federal adjudication.
  • Employees may not have an affiliation with a foreign government identified by the Department of Energy as a country of risk without prior disclosure and approval or recusal.

Responsibilities

  • Lead applied research for national-security applications, designing evaluation harnesses, developing novel test and evaluation methods, and shaping technical direction for large programs.
  • Own defined evaluation workstreams or small-to-medium projects evaluating large language models, vision-language models, artificial intelligence agents, agentic workflows, and integrated artificial intelligence systems for national-security missions.
  • Translate national-security mission needs into strategic test and evaluation frameworks, operational scenarios, evaluation criteria, and technical approaches for generative artificial intelligence and agentic pipelines.
  • Mentor junior staff and interns, and coordinate work across multidisciplinary teams to develop junior staff into technical leaders.
  • Assess systems at the model, component, workflow, and end-to-end levels; design evaluation plans integrating aggregate performance measures with behavioral analysis, failure characterization, data slices, robustness testing, calibration and uncertainty, and mission-context evidence.
  • Select, design, or develop evaluation environments, test harnesses, agentic harnesses, datasets, deterministic baselines, rubrics, and validated automated or model-based graders.
  • Champion collaborative data science workflows and ensure research, code, and models are version-controlled, documented, and reproducible across project teams using tools such as Git, GitLab, Jira, Confluence, and Microsoft 365.
  • Synthesize evaluation results, operational constraints, and uncertainties into technical reports, documentation, and peer-reviewed publications; present research at technical conferences through accepted papers or invited talks.
  • Deliver briefings for technical and non-technical stakeholders that connect technical findings to mission impact; lead discussions and brief sponsors and domain experts to inform project direction.
  • Lead business development and proposal efforts to secure funding aligned with or expanding the division’s artificial intelligence research and test-and-evaluation capabilities.
  • Travel for project events as required.

Desired Qualifications

  • Experience as a principal investigator of federally funded research and development projects, or owning an evaluation workflow or small-to-medium technical project involving large language models, vision-language models, or artificial intelligence agents.
  • Experience developing and leading the design of evaluation environments, agentic harnesses, behavioral tests, validated graders, or continuous-evaluation pipelines, including large-language-model-as-a-judge methods or evaluation agents.
  • Experience analyzing model behavior beyond aggregate performance metrics, including failure modes, data-slice performance, robustness, generalization, calibration, uncertainty, or distribution shift.
  • Experience evaluating systems combining generative artificial intelligence with deterministic natural language processing, computer vision, retrieval, knowledge graphs, rules, or analytical tools.
  • Strong experience using Python and frameworks such as PyTorch to conduct reproducible machine-learning research.
  • Robust experience with version control using Git and collaborative software development practices to maintain reproducible research repositories.
  • Evidence of applied research impact for national-security applications through peer-reviewed publications, technical reports, open-source contributions, prototypes, sponsor briefings, or transitioned capabilities.
  • Experience leading research proposals and mentoring junior technical staff into technical leaders.
  • Active Top Secret/Sensitive Compartmented Information clearance.

About the Company

Pacific Northwest National Laboratory

National lab advancing energy, security, environment

Pacific Northwest National Laboratory (PNNL) conducts scientific research in chemistry, Earth sciences, biology, and data science to advance energy resiliency and national security. Its work spans designing and running experiments, developing models and simulations, and analyzing large data sets to generate knowledge and practical tools that help improve energy systems, environmental stewardship, and security. PNNL differentiates itself through its interdisciplinary approach across multiple scientific domains and its role as a government-funded national lab focused on real-world challenges, enabling collaborations with industry, academia, and government partners. Its goal is to produce actionable scientific insights and deployable technologies that strengthen national resilience and energy infrastructure.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Richland, WA
Founded
1965

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