Responsibilities

The AI & Data Analytics division is seeking to hire a Senior Data Scientist for AI Safety applied research. 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.

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

As a Senior Data Scientist (Data Scientist 4), you will serve as a senior technical expert and leader setting technical direction and vision for AI Safety research, drive proposal development, mentor early through senior researchers, and engage directly with stakeholders. Key responsibilities include:

• Set technical direction for projects developing and applying safety methods and pipelines that analyze model internals (e.g., attention, routing, memory, tokenization, tool-use) and/or surface failure modes, capabilities, and risk profiles.
• Engage with stakeholders to translate mission needs and operational constraints into actionable safety requirements, test plans, and success criteria aligned with mission-driven goals.
• Lead projects and programs to design, implement, and validate model evaluation for cutting edge AI including frontier AI systems (e.g. LLMs, LVMs, multimodal, agentic) or development/verification of safety controls and guardrails.
• Translate cutting-edge research into mission-relevant tools and prototypes; rapidly evaluate new techniques and standards in AI safety, algorithm or system evaluation, and trustworthy AI.
• Lead development of AI safety methods across multiple axes: robustness, uncertainty quantification, manipulation, autonomy and tool-use risks, stress testing, generalization, or reliability under distribution shift.
• Build effective relationships across teams and divisions; mentor junior and senior staff; cultivate an inclusive, collaborative research culture.
• Maintain awareness of emerging trends in AI safety, AI security, alignment, national security operations, and relevant standards to shape future research directions.

Knowledge, Skills, and Abilities

• Ability to collaborate in multi-disciplinary, mission-driven teams and operate effectively in high-stakes
• 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.
• 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.
• 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.
• Strong stakeholder engagement skills and the ability to connect technical safety work to operational mission outcomes.
• Proven track record delivering AI safety/evaluation work products in complex domains, including National Security.
• Hands-on experience with LLM/LVM/Foundation Model and Frontier AI evaluation, red-teaming, uncertainty analysis, or safety control implementation.
• Experience leading federally funded R&D projects, with publications, open-source contributions, or deployable prototypes.

Team & Culture

We foster a collaborative and innovative environment centered on continued learning, creative problem-solving, and responsible, data-driven innovation. You will work as part of interdisciplinary teams to deliver AI safety solutions for high-stakes, real-world applications. Our teams combine expertise in AI and machine learning, software engineering, human-centered design, and national security missions.

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

Qualifications

Minimum Qualifications:

• 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

Preferred Qualifications:

• Experience serving as PI, technical lead, or project manager on multi-institution R&D efforts.
• Demonstrated impact in safe and trustworthy AI (e.g., peer-reviewed publications, recognized awards, contributions to community standards).
• Familiarity with agentic AI safety (tool-use governance, retrieval hygiene, autonomous decision workflows) and evaluation of multi-step reasoning systems.
• Experience with privacy-preserving ML (e.g., differential privacy, federated learning), robust training methods, and secure data lifecycle practices.
• Background working with or mapping to relevant frameworks/standards (e.g., AI safety/testing best practices, risk management frameworks) and translating them into test and evaluation plans.
• Prior work in national security environments, with an understanding of mission needs and operational constraints.
• Active DOE Q or TS/SCI clearance.

Hazardous Working Conditions/Environment

Not applicable.

Additional Information

This position requires the ability to obtain and maintain a federal security clearance.