Principal Embedded Edge AI Engineer

Johnson Controls • Glendale, AZ

2d • Onsite

About The Position

Join our Data Center Cooling Optimization team as a Principal Embedded Edge AI Engineer, where you will design and deploy advanced AI/ML models—including LLM/SLM‑style architectures—directly onto embedded and edge platforms that control mission‑critical cooling systems. You will work at the intersection of data science, embedded software, and real‑time control, developing time‑series intelligence, anomaly detection, and predictive maintenance models that operate under strict latency, compute, and reliability constraints. This role requires deep technical expertise and the ability to guide system‑level decisions across software, controls, and hardware teams. This position is 100% on‑site at our new Controls Product Development Center and Lab in Glendale, WI, where you’ll collaborate closely with cross‑disciplinary teams and work hands‑on with real products. The role may include up to 20% travel .

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
• Strong background in time‑series ML and deep learning architectures
• Proficiency with TensorFlow or PyTorch
• Strong C/C++ skills for embedded or performance‑critical paths
• Experience deploying ML models on edge devices or embedded systems
• Familiarity with reliability engineering (FMEA, PHM)
• Ability to work under minimal supervision and guide technical decisions
• Excellent communication and cross‑functional collaboration skills

Nice To Haves

• Experience with digital twins and reinforcement learning for control
• Experience with LLM/SLM‑style architectures optimized for edge
• Experience with IoT protocols and edge compute frameworks
• Experience with data‑center systems, HVAC, or thermal management
• Rust programming experience
• Experience with model compression, quantization, or hardware acceleration

Responsibilities

• Develop and deploy AI/ML on embedded and edge devices
• Build time‑series models for load estimation, anomaly detection, and RUL/condition‑based maintenance
• Implement TensorFlow or PyTorch models optimized for edge execution
• Develop embedded inference pipelines in C/C++ (Rust a plus)
• Collaborate with data scientists to translate research models into production‑ready embedded implementations
• Work with IoT and controls teams to integrate ML outputs into real‑time control loops
• Optimize models for latency, memory footprint, and power constraints
• Apply FMEA, SFMEA, and PHM principles to ensure reliability and safety
• Lead system‑level debugging, validation, and performance tuning
• Mentor engineers and influence technical direction across the organization

Benefits

• Competitive salary
• Paid vacation/holidays/sick time
• Comprehensive benefits package including 401K, medical, dental, and vision care
• On-the-job/cross-training opportunities
• Encouraging and collaborative team environment
• Dedication to safety through our Zero Harm policy
• Competitive Bonus plan
• Competitive benefits package

What This Job Offers

• Job Type: Full-time
• Career Level: Principal