Define and evolve the multi-year architecture for power control systems across Apples product lines Design and specify control algorithms - classical, modern, and data-driven - for battery, thermal, and performance constraints operating across multiple timescales Guide algorithm implementation from concept through embedded deployment, partnering with firmware and systems teams Analyze real-world performance/power data to identify architecture and algorithm improvements, including opportunities for predictive, machine-learning-informed power allocation Review and approve control system designs across the power control system domain Mentor engineers and help set technical direction for the power control systems teamBS degree Experience with one or more of the following programing languages: Matlab/Simulink, C/C++, Bash and/or Python Experience with control system design in one or more of the following areas: Classical Control Theory, Modern Control Theory, System Identification, Estimation Theory, Signal Processing, or multi-timescale constraint handlingMS or PhD in Electrical/Computer Engineering or Computer Science or equivalent 20+ years of relevant industry experience Experience implementing control systems in embedded microcontroller environments Experience applying data-driven or machine-learning approaches to power allocation, predictive analytics, or constraint prediction Experience with multi-timescale or hierarchical constraint-handling techniques in real-time control systems Innovative and critical system-level thinker with control system design and debug skills Desire to bring data-driven decision-making and analytics to improve our products Professional and collaborative with interpersonal communication skills. This work involves collecting and analyzing performance/power data from real-world workloads, applying advanced control theory and estimation techniques to multi-timescale constraint problems, exploring data-driven and predictive approaches to power allocation, cooperating with systems and software teams to characterize and analyze power/performance profiles, and evaluating power control algorithms based on the resulting insights.