Apple
Machine Learning Engineer - On-Device Control and Optimization
$142K–$263K
Seattle, Washington · Full-time · Posted Aug 21, 2026
- Education
- MS or PhD in controls, robotics, electrical engineering, computer science, or another quantitative field — or BS with relevant experience.
About the job
Develops and deploys on-device machine learning and control systems that manage power and energy tradeoffs across Apple devices.
What you'll do
- Analyze raw device logs and field data to understand behavior, identify opportunities, and validate models.
- Model device power and energy dynamics using lab and field data; develop and evaluate ML and control systems.
- Prototype end-to-end systems from data analysis through deployment, working with firmware, hardware, and platform teams.
What they ask for
- Experience with model predictive control, optimal control, or reinforcement learning (sequential decision-making).
- Experience working with raw logs or sensor data and building analysis from scratch.
- Strong Python skills.
- Ability to take a project from data exploration through a working prototype.
Nice to have
- Experience with thermal systems, battery management, or energy optimization.
- Familiarity with embedded or resource-constrained environments; hands-on ML experience and a track record of shipping models or control systems are also preferred.
Pay
$142,300 and $263,300 (base salary)
Tools
Python
AI focus
Build, evaluate, and deploy machine learning and control systems on-device to manage power and energy tradeoffs.
Model-written summary · the original posting is authoritative