Machine Learning Engineer II

Sourced from ces.pugetsound.edu

PNNL's AI and Data Analytics Division seeks a Machine Learning Engineer to implement and adapt research methods within shared software used by U.S. government stakeholders. The role focuses on deep learning for large language models and computer vision, spanning AI Assurance, agentic AI, and applied mathematics. You will build reusable packages and APIs, refactor experimental code, and develop tests and evaluations in collaboration with researchers. The position is based in Richland or Seattle, WA and requires onsite presence plus eligibility for a federal security clearance.

• Implement and adapt deep learning and computational methods with researchers, debugging implementation and model behavior
• Independently develop, test, and maintain defined software components within the broader architecture
• Implement and maintain agentic AI workflow components, including model tool calling and API/data source integration
• Build reusable packages, APIs, and interfaces connecting research methods to sponsor systems
• Refactor experimental code for clarity, performance, and maintainability
• Develop tests and evaluations comparing implementations with research results
• Use reproducible environments, dependency management, automated testing, and documentation
• Participate in code reviews and coordinate changes in shared codebases

• BS/BA with 2 years of data science experience, or MS/MA, or PhD
• Experience using Python with PyTorch, TensorFlow, or a similar deep learning framework
• Experience implementing or adapting methods for large language models, computer vision, or related deep learning applications
• U.S. Citizenship and ability to obtain and maintain a federal security clearance
• Ability to work onsite in Richland, WA or Seattle, WA

• Experience with modular software design, automated testing, version control, and collaborative development
• Experience building or adapting agentic AI applications, including workflow orchestration, tool integration, or tracing multi-step behavior
• Experience interpreting technical literature and collaborating with researchers, particularly in AI Assurance, agentic AI, or applied mathematics
• Experience developing reusable packages or APIs and integrating them into larger systems
• Experience deploying and maintaining ML or computational software with reproducible environments and automated build/deployment workflows
• Experience supporting national security missions