Lead Machine Learning Engineer IV

Overview At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget. Our Science & Technology directorates include National Security, Integrated Discovery Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus. The National Security Directorate (NSD) drives science-based, mission-focused solutions to take on complex, real-world threats to our nation and the world. The AI and Data Analytics Division, part of the National Security Directorate, combines profound domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytic challenges. Working in multidisciplinary teams, we connect foundational research to engineering to operations, providing the tools to innovate quickly and field results faster. Our strengths are integrated across the data analytics lifecycle, from data acquisition and management to analysis and decision support. Responsibilities PNNL is seeking a Lead Machine Learning Engineer to lead the development and evolution of software that brings emerging research methods into sponsor environments. You will work with researchers, engineers, and U.S. government stakeholders to shape technical approaches, resolve difficult implementation and integration challenges, and guide shared software through deployment and continued improvement. You will contribute directly to shared codebases, from experimental implementation through deployment primarily in unclassified sponsor environments. The team maintains and improves the software over time. The work focuses on deep learning methods for large language models and computer vision. Projects span research areas such as AI Assurance, agentic AI, and applied mathematics, with opportunities to work with other models and methods. You will lead through project teams, remain hands-on in technical work, and help engineers grow through mentoring, feedback, and opportunities to take on greater responsibility. Key Responsibilities • Set architecture and engineering direction for complex software capabilities involving multiple components, contributors, and stakeholder needs. • Guide the architecture and implementation of agentic AI systems across shared codebases, working with researchers and engineers to resolve tradeoffs involving model and tool integration, workflow orchestration, reliability, and sponsor deployment constraints. • Work with researchers to interpret and adapt emerging methods, resolving difficult tradeoffs among research intent, implementation behavior, performance, and deployment constraints. • Contribute directly to consequential implementation and debugging work, including deep learning methods in PyTorch. • Lead software evolution through development, deployment, and continued maintenance, coordinating technical plans, dependencies, and contributions across project teams. • Align interfaces and implementation approaches across shared codebases with researchers, engineers, and U.S. government stakeholders. • Guide testing and evaluation approaches that verify algorithmic behavior, integration, and reliability as methods and software change. • Guide reproducible development and release practices, including dependency management, automated testing, documentation, and compatibility across components. • Develop engineers through design discussions, code reviews, sustained mentoring, and opportunities to take on greater responsibility. • Shape technical plans and contribute to proposals with collaborators to support continued software development and new capabilities. • Conduct work in secure environments in accordance with operational security requirements. This position is based in either Richland, WA or Seattle, WA and requires an onsite presence. Qualifications Minimum Qualifications: • BS/BA and 7+ years of data science experience -OR- • MS/MA and 5+ years of data science experience -OR- • PhD with 3+ years of data science experience. • 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. Preferred Qualifications: • Experience leading software architecture, design, and implementation across multiple components and stakeholders, including guiding technical decisions and mentoring engineers. • Experience leading the development and evolution of agentic AI systems, including reusable components, evaluation, observability, and deployment across multiple contributors or projects. • Experience interpreting technical literature or mathematical descriptions, discussing assumptions with researchers, and implementing, adapting, or debugging methods for research and deployment, particularly in AI Assurance, agentic AI, or applied mathematics. • Experience maintaining and evolving shared software, including managing interfaces, dependencies, and integration changes, with practices for testing, reproducible development, code review, and releases. • Experience coordinating software development across organizations or with U.S. government stakeholders, deploying and improving software in sponsor environments, or developing technical plans and proposals for research or software development. • Experience supporting national security missions. Hazardous Working Conditions/Environment Not applicable. Additional Information This position requires the ability to obtain and maintain a federal security clearance. A security clearance background investigation includes review of your employment, education, financial, and criminal history, as well as interviews with you and your per