Pacific Northwest National Laboratory

Benefits

• Dental Insurance
• Disability Insurance
• Employee Assistance Program
• Equity
• Health Insurance

Skills

Requirements

• Set technical direction for projects developing and applying safety methods and pipelines
• Engage with stakeholders to translate mission needs and operational constraints into actionable safety requirements
• Lead projects and programs to design, implement, and validate model evaluation for cutting edge AI
• Translate cutting-edge research into mission-relevant tools and prototypes

Benefits

• 401k Matching
• Certification Support
• Company Retreats
• Conference Budget
• Dental Insurance
• Disability Insurance
• Employee Assistance Program
• Employee Discounts

Skills

Requirements

• Lead large, multi-year research and development programs
• Shape national technical direction
• Mentor interdisciplinary teams
• Collaborate closely with software engineers
• Serve as a key interface with sponsors and stakeholders
• Align PNNL's research agenda with evolving mission requirements
• Drive real-world impact
• Contribute to impactful, mission-focused applied R&D projects

Benefits

• 401k Matching
• Certification Support
• Company Retreats
• Conference Budget
• Dental Insurance
• Employee Assistance Program
• Employee Discounts
• Flexible Hours

Skills

Requirements

• Designs and executes rigorous ML experiments following community best practices
• Evaluates AI systems across multiple dimensions
• Analyzes the internal structures and representations of deep learning models
• Writes high-quality, well-documented research code
• Contributes to publications and technical reports
• Collaborates with senior researchers, engineers, and cross-functional teams
• Conducts work in secure environments with adherence to operational security requirements

Benefits

• 401k Matching
• Health Insurance
• Paid Time Off
• Performance Bonus
• Professional Development
• Retirement Plan
• Training Budget

Skills

Requirements

• Defines and leads research agendas in areas such as explainable AI, adversarial machine learning, AI safety, and the science of deep learning.
• Designs and executes rigorous ML experiments at scale, including large-scale training and evaluation on HPC infrastructure.
• Develops novel evaluation methodologies that go beyond standard performance metrics to assess generalization, robustness, and out-of-distribution behavior.
• Analyzes the internal structures and representations of deep learning models, with emphasis on large language models and large vision models.
• Interprets empirical results to identify promising research directions and guide strategic investment of team resources.
• Establishes best practices for research code quality, reproducibility, and integration into operational pipelines.
• Mentors junior researchers and engineers, fostering a culture of scientific rigor and collaborative inquiry.

Benefits

• 401k Matching
• Health Insurance
• Paid Time Off
• Performance Bonus
• Professional Development
• Retirement Plan
• Training Budget

Skills