Safety Ai Data Trainer Jobs (NOW HIRING)

Job Summary:
Pacific Northwest National Laboratory (PNNL) is a world-class research institution focused on scientific research and innovation. They are seeking a Senior Data Scientist for AI Safety applied research to lead projects that address complex challenges at the intersection of artificial intelligence and national security.
Responsibilities:
• 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.
Qualifications:
Required:
• 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.
• 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.
• 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.
Preferred:
• 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.
Company:
Pacific Northwest National Laboratory operates as a government research laboratory. Founded in 1965, the company is headquartered in Richland, USA, with a team of 5001-10000 employees. The company is currently Late Stage.