Autonomous Building AI Engineer

Aimlroles; Holladay (UT); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical, dental, and vision coverage

Disability and life insurance options

Flexible paid time off

Free catered lunch in the office

Free National Parks pass

Free ski pass

Job summary

PassiveLogic seeks a Physical AI Engineer to develop, validate, and optimize autonomous control systems for buildings. You’ll build production-grade AI models, digital twins, and autonomy levels to understand physical states and improve performance in real environments.

You will work across control theory, machine learning, and physics-based simulation, validating algorithms in simulation, lab setups, and real buildings with a focus on reliability and real-time operation.

Qualifications

• MS or PhD in control engineering, computer science, robotics, applied mathematics, mechanical engineering, or a related field.
• Expertise in AI development, scientific machine learning, optimal control, reinforcement learning, multi-agent systems, physics-informed machine learning, and optimization theory.
• Strong background in control theory, model predictive control, state estimation, and system identification.
• Strong programming skills in Python, C++, Swift, or a similar language.

Responsibilities

• Develop autonomous control strategies using physics-based digital twins for prediction, optimization, and decision-making.
• Translate comfort, energy, equipment life, and operational requirements into control objectives, constraints, and cost functions.
• Develop scalable optimization algorithms (e.g., stochastic gradient descent, coordinate descent, distributed optimization, Bayesian methods, evolutionary algorithms).
• Design and implement physics-based automated fault-detection and diagnosis algorithms.
• Develop fault-tolerant control methods enabling degraded operation and recovery.
• Integrate control and learning algorithms into production systems with reliability and real-time performance.

Skills

AI development

Scientific ML

Optimal control

Reinforcement learning

Multi-agent systems

Physics-informed ML

Optimization theory

Education

MS/PhD in relevant field

Tools

Python

C++

Swift

Job description

PassiveLogic seeks a Physical AI Engineer to develop, validate, and optimize autonomous control systems for buildings. You’ll build production-grade AI models, digital twins, and autonomy levels to understand physical states and improve performance in real environments.

You will work across control theory, machine learning, and physics-based simulation, validating algorithms in simulation, lab setups, and real buildings with a focus on reliability and real-time operation.