How to apply for QUEST, EnergyPlus Energy Modeler Intern (Unpaid)

About ClimateForge

ClimateForge is a lean energy modeling and software infrastructure startup that builds AI-driven tools to accelerate sustainable building design. Working here means direct ownership of high-impact projects at the intersection of climate tech, building science, and modern software—ideal for someone who wants to shape early-stage products rather than maintain legacy systems.

About the role

As a QUEST/EnergyPlus Energy Modeler Intern, you'll work at the code level to transform and improve energy and building designs, likely by scripting simulations, parsing IDF files, and integrating AI workflows into model pipelines. Your work will directly speed up ClimateForge's ability to deliver sustainable design insights, making this a high-leverage role despite being unpaid.

A typical day

You might start by writing a Python script to batch-run EnergyPlus simulations across dozens of design variants, then debug an IDF parsing issue that's causing incorrect outputs. Later, you'd collaborate asynchronously with the team to integrate those results into an AI-driven recommendation tool, and document your workflow for future interns. Expect a mix of coding, model troubleshooting, and quick iteration on climate-impact projects.

Who ClimateForge is looking for

• Comfortable writing and debugging Python scripts that generate, modify, or parse EnergyPlus IDF and QUEST model files—not just clicking through a GUI.
• Has hands-on experience with building energy simulation concepts: HVAC systems, envelope performance, schedules, weather files, and simulation outputs like EUI or unmet load hours.
• Understands the software architecture behind tools like EnergyPlus and QUEST (e.g., input/output schemas, APIs, command-line execution, version differences) and can automate model runs.
• Self-directed and eager to take ownership of AI application features in a fast-moving remote startup, with strong written communication for async collaboration.

Tips for this application

• In your application, name specific EnergyPlus objects or IDF file sections you've worked with (e.g., Building, Zone, HVACTemplate, Output:Variable) to prove you understand the software at the code level, not just the UI.
• Link to a GitHub repo or portfolio showing Python scripts that automate EnergyPlus runs, parse .eso/.csv outputs, or manipulate IDF files—this is the strongest signal for this role.
• Mention QUEST by name and describe how you've used it beyond the interface, such as importing/exporting models, scripting, or comparing its simulation engine to EnergyPlus.
• Since the internship is unpaid, briefly explain your motivation for climate-impact work and how this role fits your learning goals, so ClimateForge sees you as mission-aligned rather than just résumé-building.
• Address the remote setup directly: highlight your ability to work independently, communicate asynchronously, and manage your own schedule while contributing to critical projects.

What to cover in your cover letter

Emphasize (1) your code-level fluency with EnergyPlus and QUEST, including any automation or scripting you've done; (2) a concrete example of improving a building energy model's speed, accuracy, or workflow; (3) your Python skills applied to simulation data or AI integration; and (4) your genuine interest in ClimateForge's mission to bring AI to sustainable building design.

Research before applying

• Explore ClimateForge's public materials to understand their specific energy modeling and software infrastructure products, and how they might use QUEST and EnergyPlus in their stack.
• Review the latest EnergyPlus documentation and GitHub repositories to refresh your knowledge of its API, Python bindings (e.g., eppy, OpenStudio), and command-line execution.
• Investigate QUEST's software capabilities, file formats, and how it differs from or complements EnergyPlus in building simulation workflows.
• Look into recent AI applications in building energy modeling (e.g., surrogate models, automated calibration) to speak intelligently about how ClimateForge could leverage AI.

Likely interview topics

Based on the job description, expect questions about:

• Walk us through how you would programmatically modify an EnergyPlus IDF file to test a set of envelope or HVAC design alternatives.
• What are the key differences between working with QUEST and EnergyPlus at the software/API level versus through their user interfaces?
• Describe a time you used Python to automate an energy modeling task—what libraries or methods did you use, and what was the outcome?
• How would you approach integrating an AI application into an existing energy modeling workflow at ClimateForge?
• Given that this is an unpaid internship, what specifically motivates you to contribute to climate tech and building energy efficiency right now?

Common mistakes to avoid

• Presenting only UI-based experience with EnergyPlus or QUEST—this role explicitly requires software-level knowledge, so avoid implying you only know the interfaces.
• Submitting a generic cover letter that doesn't mention ClimateForge, QUEST, EnergyPlus, or the unpaid nature of the internship, which signals a lack of attention to the specific opportunity.
• Focusing solely on academic coursework without showing any self-driven projects, scripts, or GitHub evidence of programming and energy modeling integration.