On-Device ML & Control Engineer: Thermal & Energy

Apple Inc.; Seattle (WA); On-site; USD 142,000 - 214,000; Full time

Job summary

Apple Inc. in Seattle, Washington, is seeking a Machine Learning Engineer for the Energy Tech organization to develop on-device control systems that manage thermal and energy tradeoffs in Apple devices.

You will prototype MPC and related control algorithms, analyze field data to understand device behavior, and collaborate with firmware, hardware, and platform teams to ship reliable, production-ready solutions.

Qualifications

• MS or PhD in controls, robotics, electrical engineering, computer science, or related field — or BS with relevant experience.
• Experience with model predictive control, optimal control, or reinforcement learning.
• Strong programming skills in Python; comfort with C/C++ for on-device work.
• Experience working with real-world sensor data.
• Demonstrated ability to take a project from data exploration through working prototype.

Responsibilities

• Design and implement on-device control systems for thermal and energy management
• Build and fit thermal models from lab and field data
• Prototype MPC and related control algorithms end-to-end, from data analysis through on-device deployment
• Analyze large-scale field telemetry to characterize device behavior and validate models
• Define and tune cost functions that encode system-level tradeoffs
• Collaborate with firmware, hardware, and platform teams to integrate control systems into the OS

Skills

Python

C/C++

Model predictive control

Reinforcement learning

Data analysis

On-device ML

Education

MS/PhD in controls/robotics/EE/CS, or BS with experience

Job description

Apple Inc. in Seattle, Washington, is seeking a Machine Learning Engineer for the Energy Tech organization to develop on-device control systems that manage thermal and energy tradeoffs in Apple devices.

You will prototype MPC and related control algorithms, analyze field data to understand device behavior, and collaborate with firmware, hardware, and platform teams to ship reliable, production-ready solutions.