Autonomous Building AI Engineer

PassiveLogic; Holladay (UT); On-site; USD 130,000 - 190,000; Full time

Benefits offered by this job

Competitive compensation

Generous equity share

Medical, dental and vision coverage

Disability and life insurance

Flex PTO

Team-building events

Free catered lunch

Free ski pass

National Park pass

Onsite gym

Job summary

PassiveLogic is seeking a Physical AI Engineer to develop and validate autonomous control systems for building environments. You will design algorithms that let buildings understand their state, learn from data, and optimize operations in real time.

The role spans control theory, optimization, ML, and physics-based simulation. You will work on digital twins, autonomous reasoning, and testing in real buildings alongside a team of engineers and researchers.

Qualifications

• MS or PhD in control engineering, CS, robotics, applied math or related field.
• Expertise in AI development, ML, optimal control, RL, multi-agent systems, physics-informed ML.
• Strong background in control theory, MPC, state estimation, system identification.
• Strong programming skills in Python, C++, Swift or similar language.

Responsibilities

• Develop autonomous control strategies using physics-based digital twins for prediction and decision-making.
• Develop physics-informed predictive and learning models using DL, RL, and transfer learning.
• Define performance metrics, tests, and acceptance criteria for autonomous capabilities across levels of autonomy.
• Test systems in simulation, labs, and real buildings; ensure reliability and real-time performance.

Skills

AI development

control theory

state estimation

model predictive control

reinforcement learning

Python programming

C++ programming

Education

MS or PhD in relevant field

Tools

Dymola

EnergyPlus

Python

Job description

PassiveLogic is seeking a Physical AI Engineer to develop and validate autonomous control systems for building environments. You will design algorithms that let buildings understand their state, learn from data, and optimize operations in real time.

The role spans control theory, optimization, ML, and physics-based simulation. You will work on digital twins, autonomous reasoning, and testing in real buildings alongside a team of engineers and researchers.