Watch EE - System Power Analysis Engineer

Santa Clara Valley (Cupertino), California, United States


Weekly Hours: 40
Role Number:200202715
You enjoy the challenges of hardware debugging and characterization, test architecture and execution, and data analytics. You will facilitate the power analysis from architecture design concept all the way to system evaluation at product ramp, aiming at delivering a world-class user experience for Apple Watch. If you are a creative and hands-on problem solver who enjoys critical thinking, applying knowledge, and learning new things, come join our team.

Key Qualifications

  • We seek a problem solver who is a thinker, detail oriented, and innately curious
  • Team collaborator with excellent interpersonal skills who thrive in a cross-functional environment
  • Possess phenomenal electrical engineering fundamentals for grasping schematics, system architecture, and circuits
  • Hands-on experience with bench measurements and lab equipment (current sensing, IV characterization, oscilloscopes, power supplies)
  • Experience with data processing and visualization
  • Good foundation in Python, or other scripting language
  • Familiarity with control loop theory, ADCs, and amplifier circuits
  • Talented at handing both software and hardware issues
  • You enjoy travel overseas


Your emphasis is cross-functional collaboration, across both SW and HW teams to address risks and concerns for power management. You will provide valuable feedback for power saving opportunities during the Watch hardware and software development cycle, and find ways to improve modeling and validation methodologies. - Develop validation plan and deliver results to address design concerns - Characterize system-level power estimates for various dynamic usage scenarios for design tradeoffs (e.g. battery life, thermal, and peak power) - Validate subsystem power against design expectations - Hands-on debug of failures and at-scale data collection to help drive investigation on system power related issues - Build automation using a combination of internal HW tools, custom SW libraries, and external SW packages to improve test robustness and repeatability - Parse and post-process data, applying data-driven analysis to interpret results, and determine impact to the system and user

Education & Experience

A BS or MS degree in Electrical Engineering, or Computer Engineering is strongly preferred. Equivalent experience with a degree in another field, such as Physics, is acceptable.

Additional Requirements

  • - Familiarity with lithium-ion battery management concepts (capacity estimation, charging algorithms, and impedance analysis)
  • - Experience integrating batteries into a shipping design
  • - Experience with system power budgeting, or creating power specifications for a component or subsystem
  • - Hardware validation experience