Senior Data Scientist IV – Gen AI Development & Evaluation

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.

The AI & Data Analytics division is seeking to hire a Senior Data Scientist. This role blends foundational research with real world implementation to address some of the most complex and consequential challenges at the intersection of artificial intelligence and national security. We support PNNL’s mission by contributing to impactful, mission focused applied R&D projects that help tackle national challenges. Successful candidates will have the opportunity to grow professionally while working on diverse, mission-focused projects.

As a Senior Data Scientist, you will also serve as a senior technical leader leading mission-driven research, driving proposal development, and engaging directly with stakeholders. This role will require hands-on experience with or leading research leveraging model internals not just inference endpoints, such as direct engagement with model architectures, training pipelines, and weight-level optimization, or developing and deploying agentic AI solutions that leverage tool use, retrieval-augmented generation, multi-step reasoning, and autonomous decision-making workflows.

Work Location & Requirements

• Based in Richland, WA or Seattle, WA with onsite presence required
• Clearance required (see below for details
• Travel may be required for stakeholder engagement or project events

Key Responsibilities

• Lead innovative projects and programs developing and applying generative AI and foundation model development (pretraining, fine-tuning, agentic systems, and innovative training strategies) and evaluation (T&E, robustness) for key modalities such as:
  • Transform hyperspectral imaging (HSI) and geospatial applications by harnessing advanced AI techniques to extract actionable intelligence from complex, multi-layered data.
  • Drive breakthroughs in multi-int fusion—integrating diverse intelligence sources to deliver robust, mission-ready solutions that elevate operational capabilities and decision-making.
  • Advance knowledge discovery, support decision intelligence, and enable robust analytical processes. This includes leveraging advanced AI techniques to extract, synthesize, and integrate insights from unstructured, semi-structured, or large-scale text and documents.
• Engage with stakeholders to understand project requirements and translate them into actionable technical approaches aligned with sponsor goals.
• Direct the design, development, and iteration on foundation model, frontier AI research, and agentic AI systems that address complex, real-world problems—especially those involving diverse data modalities such as remote sensing imagery, sensor fusion, and text.
• Apply deep expertise in model internals (e.g., tokenization, attention mechanisms, weight adaptation, and loss optimization) to customize and improve model performance for domain-specific applications.
• Lead evaluation and verification of AI and agentic systems across multiple axes, including standard performance metrics, uncertainty quantification, generalization to out-of-distribution settings, and mission-specific assurance criteria.
• Lead proposal development and business development through proposals and/or briefing sponsors.
• Serve as a technical resource and mentor to junior to senior staff within the team, fostering a collaborative research environment and mission awareness.
• Maintain awareness of emerging trends in AI, AI security, and national security to shape future research directions and identify new opportunities for impact.

Knowledge, Skills, and Abilities

• Demonstrated proficiency in leading proposals, writing technical reports, and communicating complex findings to diverse audiences (technical and executive).
• Knowledge of compute environments and their cybersecurity concerns; familiarity with secure ML ops, access control, and model/data governance.
• Demonstrated impact in Generative AI, Frontier AI, or foundation model research (e.g., peer reviewed publications, recognized awards, contributions to community standards).
• Deep knowledge of the current ML research landscape, especially AI safety, adversarial machine learning, xAI/interpretability, uncertainty quantification, and the science of deep learning.
• Hands on experience analyzing internal structures of deep learning models, particularly LLMs and large vision/multimodal models (tokenization, attention mechanisms, routing, weight adaptation, loss optimization) or modalities including hyperspectral imagery.
• Hands on experience with LLM/LVM/Foundation Model and Frontier AI evaluation, red teaming, uncertainty analysis, or safety control implementation.
• Experience designing and executing T&E campaigns for AI systems, including test planning, dataset curation, metrics, statistical analysis, and reproducibility.

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

• BS/BA and 7 years of relevant work experience -OR-
• MS/MA and 5 years of relevant work experience -OR-
• PhD with 3 years of relevant experience

• Degree in computer science, statistics, mathematics, or related fields.
• Experience serving as PI, technical lead, or project manager for federally funded R&D projects, with publications, open source contributions, or deployable prototypes.
• Knowledge of compute environments and their cybersecurity concerns; familiarity with secure ML ops, access control, and model/data governance.
• Experience designing and executing T&E campaigns for AI systems, including test planning, dataset curation, metrics, statistical analysis, and reproducibility.
• Software engineering foundations: Python, ML frameworks (PyTorch/TensorFlow), experiment tracking, and data pipeline tooling.
• Familiarity with agentic AI safety (tool‑use governance, retrieval hygiene, autonomous decision workflows) and evaluation of multi‑step reasoning systems.
• Prior work in national security environments, with an understanding of mission needs and operational constraints.
• Active DOE Q or TS/SCI clearance.

Not applicable.

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.

This position is a Testing Designated Position (TDP). 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.