Research Engineer III – AI for Building Energy Systems

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, Earth and Biological Sciences, Physical and Computational 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 Energy and Environment Directorate delivers science and technology solutions for the nation’s biggest energy and environmental challenges. Our more than 1,700 staff support the Department of Energy (DOE), delivering on key DOE mission areas including: modernizing our nation’s power grid to maintain a reliable, affordable, secure, and resilient electricity delivery infrastructure; research, development, validation, and effective utilization of renewable energy and efficiency technologies that improve the affordability, reliability, resiliency, and security of the American energy system; and resolving complex issues in nuclear science, energy, and environmental management.

The Electricity Infrastructure and Buildings Division, part of the Energy and Environment Directorate, is accelerating the transition to an efficient, resilient, and secure energy system through basic and applied research. We leverage a strong technical foundation in power and energy systems and advanced data analytics to drive innovation, transform markets, and shape energy policy.

Responsibilities

The Electricity Infrastructure and Buildings Division, part of the Energy and Environment Directorate, is accelerating the transition to an efficient, resilient, and secure energy system through basic and applied research. We leverage a strong technical foundation in power and energy systems and advanced data analytics to drive innovation, transform markets, and shape energy policy.

This position is in the Building Simulation and Design Group (BS&DG) within PNNL’s Electricity Infrastructure and Buildings Division. BS&DG conducts modeling and analysis to evaluate the impacts of building energy policies, codes, and standards; develops tools and workflows to support building research and decision making; and helps accelerate adoption of energy efficient technologies. The group maintains core research capabilities in building energy simulation, building energy policy analysis, and tool development for building applications.

BS&DG is seeking a Research Engineer III – AI for Building Energy Systems. The successful candidate will be accountable to Project and/or Task Managers for performing assigned roles, following applicable project and field procedures, and completing assigned tasks on time and within budget. The candidate will also be accountable to the Group Leader and Team Leader for staff performance and development, operational discipline, and project execution.

This position is based in Portland, OR, Richland, WA, or Seattle, WA and requires an onsite presence. Hybrid work arrangements may be available in accordance with laboratory policy, project needs, and team expectations.

Responsibilities

This role will serve as a technical lead for AI-enabled building energy systems research under DOE mission areas, with applications that may include building energy modeling, code compliance checking, permitting, large-scale performance data analysis, workflow automation, building controls and operations, workforce training, data mining, and AI-enabled software tools.

The successful candidate will join multi-disciplinary project teams and focus on integrating AI into building research and engineering workflows to improve speed, consistency, scalability, and productivity for internal research teams as well as external stakeholders and tool users. The candidate will also translate advances in generative AI, large language models, agentic systems, and computational methods into mission-relevant tools, workflows, and technical products for building research, analysis, and decision making.

• Conduct and lead independent research in AI-enabled building energy systems research under a given mission area, including generative AI, large language models, and agentic systems for building research applications.
• Develop, fine tune, test, evaluate, and apply generative AI, large language model, and agentic methods for building research applications, including data curation and performance and assurance evaluation.
• Lead development of analysis methods, modeling workflows, tools, and prototypes for building research applications, including integration of AI methods into software tools and technical workflows.
• Translate research into mission-relevant tools and technical products that support building research and decision making.
• Support and lead work on existing building research and engineering pro