Software Engineering Intern
Pear VCAbout the role
About us
Pearl Street's mission is to accelerate the transition to a reliable, decarbonized grid. We deliver software solutions to electric grid operators, utilities, and renewable energy project developers to tackle the "interconnection bottleneck," the process by which large-scale solar, wind, and battery projects connect to the power grid. To date, nearly 300 billion watts’ worth of renewable energy projects have been modeled in our software to expedite their interconnection to the grid – equivalent to nearly 700 million solar panels, 30 billion LEDs, or 390 million horses! If you are interested in solving the most pressing challenges of the world’s most critical infrastructure, we’d love to hear from you!
What you’ll do
We are looking for a motivated graduate student or upper-class student in computer science or engineering who is interested in learning and contributing to high-quality software in a fast-paced environment. We’re building powerful cloud software to help make it faster, easier, and cheaper for renewable energy projects to be deployed on the grid. You will have a chance to work closely with the team building out this app, with research, development, and experimental tasks in the areas of:
Deploying and testing large-scale parallel compute code on cloud-based infrastructure;
Investigating, analyzing and building models from complex data related to renewable energy projects proposed to connect to the electric grid
Working with other members of the team to define product requirements, develop tests, and validate results.
Your work will help project developers deploy more (and better) zero-carbon generation projects on the grid!
What we value
Proficiency in Python; knowledge of C++ is a plus
Experience in deploying/maintaining/debugging software on a cloud environment such as AWS is a plus
Knowledge of numerical methods for simulation and/or optimization is a plus
Knowledge of electronic design automation tools and methods is a plus
Junior/Senior BS student or MS/PhD graduate student in EE/CE/ECE/CS is preferred
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