National Renewable Energy Laboratory

Software Engineer

• Collect the required data and develop fundamental methods and software tools and interfaces required to support large scale electric system capacity expansion.
• Develop the generalized frameworks to link capacity expansion models (CEM), such as GenX and ReEDS, and production cost models (PCM), such as Sienna\Ops.
• Develop automated workflows to estimate maximum power flow transfer constraints between any arbitrary set of aggregated spatial regions (or 'zones').
• Work towards automating transmission network designs to enable generation interconnections and transmission capacity augmentations consistent with results from CEMs and develop methods for automated downscaling of zonal CEM results to a nodal PCM for further reliability analysis.

Capacity Expansion Model Developer

Full-stack Engineer

• Contribute to the full software development lifecycle, from design and prototyping to testing and deployment of applications in the Sienna platform.
• Develop new features for existing and new energy analysis applications and libraries, including planning and operational models.
• Collaborate with researchers to take technical specifications and translate them into code.
• Write documentation and unit tests to ensure code quality and maintainability.
• Participate in code reviews and team meetings, actively contributing to our agile development process.

Software Engineering Intern – Grid Modeling Applications

• Collaborate with researchers to translate complex transportation energy concepts into robust, modular, and maintainable software libraries; focus on refactoring legacy scripts into production-grade tools.
• Architect and implement high-performance computing (HPC) workflows to ingest, clean, and process large-scale geospatial and mobility datasets efficiently.
• Enhance the performance and reliability of existing tools and models; implement parallelization strategies, improve memory management, and ensure code scalability.
• Champion software engineering best practices within the research team, including implementing unit/integration testing, setting up CI/CD pipelines, and managing version control (Git) workflows.
• Create comprehensive technical documentation (e.g., Sphinx, ReadTheDocs) for developed tools; assist in the technical writing for peer-reviewed publications regarding model architecture and computational methods.

Undergraduate/Graduate Intern – Transportation Research Software Engineering

Artificial Intelligence

• Contribute to the development of software to execute power characterization experiments of AI LLM workloads under different parameter assumptions i.e. sensitivity analysis
• Performing computational experiments, running batch experiments on NLR HPC using SLURM
• Analyzing results capturing trends and tradeoffs between parameter configurations
• Coordinating data exchange to inform other team members’ efforts
• Contribute to writing and presenting reports and conference proceedings related to characterization tests

Graduate Intern – AI Data Center Workloads Characterization & Simulation

Machine Learning Engineer

• looking for a year-round intern (summer intern is also acceptable)
• work on projects developing learning-based analytics
• cyber-attack-resilient control strategies and optimizations for power distribution systems
• conducting literature review
• identifying gaps and summarizing new research opportunities
• conduct research work independently
• collaborate with project PI and other researchers from the project team

Graduate PhD Student – Machine Learning Applications for Cyber-Physical Power System Operations Intern

• Develop and implement novel mathematical optimization models (e.g., stochastic programming, robust optimization, mixed-integer linear programming) for medium-term grid planning.
• Design and code efficient algorithms for large-scale optimization problems using the Julia programming language and packages such as JuMP.jl.
• Collaborate with a multidisciplinary team of engineers, computer scientists, and data scientists to put research insights into open-source software products.
• Publish research findings in leading academic journals and present at major international conferences.
• Contribute to the development of the open-source power systems modeling software Sienna.

Capacity Expansion Model Developer

Software Engineering Intern – Grid Modeling Applications

Undergraduate/Graduate Intern – Transportation Research Software Engineering

Graduate Intern – AI Data Center Workloads Characterization & Simulation

Graduate PhD Student – Machine Learning Applications for Cyber-Physical Power System Operations Intern

Postdoctoral Researcher – Model Engineering