Building Systems Digital Twin Engineer
| Company | Passive Logic |
|---|---|
| Location | Murray, UT, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Mid Level, Senior |
Requirements
- A background in physics, mathematics, engineering or a related field.
- Knowledge of the fundamentals of building energy systems, HVAC, and building modeling.
- A background in software development with proficient experience in the programming environment, including debugging.
- Exceptional communication skills: Extraordinary teammate skills with a collaborative, interpersonal communication style. Strong customer-facing skills with an ability to clearly communicate complex technical concepts to both technical and non-technical audiences.
- Organized and strategic: Creative thinker and strong problem solver with meticulous attention to detail.
- Collaborative mindset: Experience working across teams to drive customer success. Strong self-motivation towards PassiveLogic’s mission to ’empower people through generative autonomy to solve the world’s largest climate challenges.’
- Adaptability: Comfortable in a fast-paced startup environment, eager to learn, iterate, and innovate.
- Problem solving: You own this role. When issues arise, be the empowered force that solves them, rolling-up.
Responsibilities
- Generate and validate building site and HVAC system digital twins under the Quantum standard for all customer facing deployments.
- Identify and log bugs throughout PassiveLogic’s technology ecosystem while synchronously working around those bugs to deliver the site model digital twin.
- Collaborate with multidisciplinary teams on a daily basis, including Customer Success, User Software, Quantum & Digital Twins, AI/Controls, Formal Methods, and more.
- Audit client buildings by ensuring the physics-based digital twin models are accurate and adaptable for real-time energy optimization and consumption forecasting.
Preferred Qualifications
- Experience with building energy modeling and model predictive control.
- A strong understanding of energy-efficient building systems and sustainability initiatives.
- Familiarity with AI-driven control platforms, smart building technology, or automation industry standards.
- Experience with digital twin creation and validation.