Research Engineer III - AI for Building Energy Systems
Role details
Job location
Tech stack
Job description
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 projects in these application areas, including projects with established workflows and projects transitioning toward AI-enabled approaches.
- Lead major technical tasks or small-to-medium projects with responsibility for scope, schedule, deliverables, and coordination of contributors.
- Engage sponsors and stakeholders and translate needs into technical approaches.
- Build working relationships across interdisciplinary teams and mentor junior staff, postdoctoral researchers, and students.
- Generate research ideas and shape technical approaches for proposals.
- Lead technical reports, publications, and conference presentations.
- Maintain awareness of emerging trends to help shape future research directions within the mission area.
Requirements
- BS/BA and 5+ years of relevant work experience -OR-
- MS/MA and 3+ years of relevant work experience -OR-
- PhD with 1+ year of relevant experience, * PhD in architectural engineering, building science, mechanical engineering, or a closely related field with at least 4 years of relevant experience beyond the PhD, demonstrating progressively increasing independence and responsibility.
- Demonstrated experience analyzing building energy systems, including modeling, controls, and system performance analysis, with ability to lead development of complex analytical or modeling approaches.
- Demonstrated experience developing, testing, and integrating AI or machine learning workflows into building energy modeling or engineering analysis systems.
- Strong programming and software development skills with experience developing scalable computational workflows, such as automated modeling pipelines, cloud computing, high performance computing, or containerized environments.
- Experience leading projects or major technical tasks with responsibility for scope, schedule, budget, technical deliverables, and coordination of team members.
- Demonstrated experience generating research ideas and shaping technical approaches for proposals while leading technical sections and contributing consistently to proposal writing.
- Established technical reputation with consistent records of leading technical publications.
- Demonstrated ability to represent technical work to sponsors, collaborators, and the broader research community.
Benefits & conditions
PNNL lists the full pay range for the position in the job posting. Starting pay is calculated from the minimum of the pay range and actual placement in the range is determined based on an individual's relevant job-related skills, qualifications, and experience. This approach is applicable to all positions, with the exception of positions governed by collective bargaining agreements and certain limited-term positions which have specific pay rules.
As part of our commitment to fair compensation practices, we do not ask for or consider current or past salaries in making compensation offers at hire. Instead, our compensation offers are determined by the specific requirements of the position, prevailing market trends, applicable collective bargaining agreements, pay equity for the position type, and individual qualifications and skills relevant to the performance of the position.
Minimum Salary
USD $112,500.00/Yr.
Maximum Salary
USD $168,600.00/Yr.