Data Scientist - Evaluating Foundation Models and AI Agents for National Security

Pacific Northwest National Laboratory; Kennewick (WA); On-site; USD 120,000 - 180,000; Full time

Job summary

Pacific Northwest National Laboratory seeks a Data Scientist in the AI and Data Analytics Division to design and run evaluation studies for AI/ML systems and agents. You will build test data, prompts, and scenarios, and create reproducible workflows and benchmarks.

Responsibilities include executing controlled experiments, analyzing model behavior, and documenting methods and results to support mission-relevant criteria. Onsite work in Richland or Seattle, with security clearance requirements.

Qualifications

• Minimum qualifications include a BS/BA with 2 years data science experience or an MS/MA or PhD.
• Experience developing or evaluating LLMs, VLMs, pretrained transformer models, AI agents, or integrated AI systems.
• Experience using Python and machine-learning frameworks (e.g., TensorFlow, PyTorch).

Responsibilities

• Design and implement evaluation studies for AI/ML systems including pretrained models and AI agents.
• Prepare datasets, prompts, scenarios, baselines, and scoring rubrics for rigorous assessment.
• Develop evaluation environments, test harnesses, and agentic components to exercise models and workflows.
• Execute controlled experiments at model, component, workflow, and system levels.
• Analyze model behavior to identify capabilities, weaknesses, and data sensitivity.
• Document methods, results, uncertainties, and limitations in reproducible code and reports.

Skills

LLMs evaluation

AI agents integration

Data analysis

Education

BS/BA in related field

MS/MA in related field

PhD

Tools

Python

TensorFlow/PyTorch

LangGraph

Job description

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-worldthreats to our nation and the world.

The AI and Data Analytics Division, part of 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.

Read more about the AI & Data Analytics division:https://www.pnnl.gov/ai-and-data-analytics

Responsibilities

As a Data Scientist in the AI and Data Analytics Division, you will work with experienced technical staff to design and implement evaluation studies, prepare mission-representative test data and scenarios, develop evaluation components and agentic harnesses, execute controlled experiments, and analyze model behavior. The work extends beyond aggregate benchmark scores to examine individual cases, meaningful data slices, component interactions, system performance under realistic operating conditions, and more. Depending on project needs, research may also address explainable AI, interpretability, or targeted mechanistic-interpretability questions.

Key Responsibilities:

• Implement defined test and evaluation activities for AI/ML with particular focus on pretrained transformer-based foundation models, including large language models (LLMs), vision-language models (VLMs), and the AI agents and systems that use them.
• Prepare evaluation datasets, prompts, mission scenarios, meaningful data slices, test cases, scoring rubrics, and deterministic baselines.
• Develop evaluation environments, test harnesses, and agentic harnesses used to exercise models, tools, retrieval systems, and end-to-end workflows.
• Execute controlled experiments at the model, component, workflow, and system levels.
• Analyze model behavior to identify capabilities, systematic weaknesses, failure modes, and sensitivity to data characteristics, retrieval results, tools, and operating conditions.
• Examine agent trajectories, intermediate decisions, tool calls, retrieved evidence, memory or state, error propagation, recovery behavior, and points of human intervention.
• Evaluate performance using aggregate metrics together with case-level analysis, behavioral categories, robustness testing, calibration and uncertainty characterization, and adversarial or off-nominal scenarios.
• Evaluate hybrid systems that combine generative AI with deterministic NLP, computer vision, retrieval, search, rules, or classical machine-learning methods.
• Help develop and validate automated or model-based graders against human judgments and mission-relevant criteria.
• Apply functional explainability, model probing, or selected interpretability methods for understanding model and system behavior.
• Document evaluation methods, assumptions, results, uncertainties, and limitations in reproducible code, visualizations, technical reports, and briefings.
• Contribute technical material, data, figures, demonstrations, or preliminary results to proposals and sponsor engagements.

Work Location & Requirements:

• This position is based in Richland, WA or Seattle, WA and requires an onsite presence.
• This position requires the ability to obtain and maintain a federal security clearance.(see below for details)

Qualifications

Minimum Qualifications:

• BS/BA and 2 years of data science experience -OR-
• MS/MA -OR-
• PhD
• Experience developing or evaluating LLMs, VLMs, pretrained transformer models, AI agents, or integrated AI systems.
• Experience using Python and machine-learning frameworks.

Preferred Qualifications:

• Experience building evaluation datasets, test harnesses, agentic harnesses, automated graders, behavioral tests, or analysis pipelines.
• Experience analyzing model behavior, failure modes, robustness, calibration, uncertainty, or performance across meaningful data slices.
• Familiarity with agent orchestration frameworks such as LangGraph or similar technologies involving routing, retrieval, tools, memory, state, and human oversight.
• Experience with deterministic NLP, computer vision, retrieval, search, rules, or classical machine-learning methods that complement generative AI.
• Experience in one or more related areas such as explainable AI, model probing, mechanistic interpretability, AI security, red teaming, uncertainty quantification, or privacy-preserving AI.
• Experience contributing to applied research through technical reports, publications, prototypes, or open-source software.
• Prior experience supporting government, national security, or other high-consequence applications.
• Active TS/SCI clearance.

Hazardous Working Conditions/Environment

• Travel may be required for project events.

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 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.