Principal Embedded Edge Ai Engineer

Johnson Controls

Glendale, WI, United States
Base: $110,000 - $164,000; bonus/equity: competiti...
On-site
Embedded ai/ml
Edge inference
Time-series ml
Johnson Controls is seeking a Principal Embedded Edge AI Engineer for their Glendale, WI location, focusing on deploying AI/ML models on embedded systems for cooling optimization. The role demands expertise in time-series intelligence and collaboration across disciplines, with a commitment to employee well-being and development

Job Summary

  • Build and deploy AI/ML models, including LLM/SLM architectures, onto embedded and edge platforms for mission-critical cooling systems.
  • Develop time-series intelligence, anomaly detection, and predictive maintenance models optimized for strict latency, compute, and reliability constraints.
  • Collaborate with cross-disciplinary teams, mentor engineers, and influence technical direction in a 100% on-site role at the Controls Product Development Center and Lab.

Matching Summary

Match Score: 85

Johnson Controls is seeking a Principal Embedded Edge AI Engineer for their Glendale, WI location, focusing on deploying AI/ML models on embedded systems for cooling optimization. The role demands expertise in time-series intelligence and collaboration across disciplines, with a commitment to employee well-being and development.

Salary

Base: $110,000 - $164,000; Bonus/Equity: Competitive Bonus plan; Benefits: Comprehensive benefits package

Skills & Requirements

Must-have

  • Embedded AI/ML
  • Edge inference
  • Time-series ML
  • TensorFlow or PyTorch
  • C/C++ for embedded
  • Reliability engineering (FMEA, PHM)

Nice-to-have

  • Digital twins and reinforcement learning
  • LLM/SLM architectures for edge
  • IoT protocols
  • Data-center systems, HVAC
  • Rust programming experience

Key Requirements

  • Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or related field
  • 4+ years of experience in embedded AI/ML, edge inference, or related fields
  • Experience deploying ML models on edge devices or embedded systems
  • Ability to work under minimal supervision and guide technical decisions

Work Rights

Not specified

Tailored Resume

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