Senior Data Scientist IV – Gen AI Development & Evaluation

Pacific Northwest National Laboratory•Richland, WA

3d•Onsite

About The Position

The AI and Data Analytics Division, part of the National Security Directorate at PNNL, is seeking to hire a Senior Data Scientist. This role focuses on blending foundational research with real-world implementation to address complex challenges at the intersection of artificial intelligence and national security. The division supports PNNL’s mission by contributing to impactful, mission-focused applied R&D projects that tackle national challenges. Successful candidates will have opportunities for professional growth while working on diverse, mission-focused projects. As a Senior Data Scientist, you will also serve as a senior technical leader, guiding mission-driven research, driving proposal development, and engaging directly with stakeholders. This role requires hands-on experience with or leadership in leveraging model internals (e.g., model architectures, training pipelines, weight-level optimization) or developing and deploying agentic AI solutions that utilize tool use, retrieval-augmented generation, multi-step reasoning, and autonomous decision-making workflows.

Requirements

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
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.
U.S. Citizenship
Ability to obtain and maintain a federal security clearance.
Must pass a Federal background investigation.
Must pass pre-employment drug testing and be subject to random drug testing.
Must demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the requisite Questionnaire for National Security Positions (QNSP).

Nice To Haves

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.
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.

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 hyperspectral imaging (HSI) and geospatial applications, multi-int fusion, and knowledge discovery.
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 like 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.