Simulation and Control Systems Engineer - Platform Architecture

Apple's Platform Architecture team is looking for a Simulation and Control Systems Engineer with a strong software background to help develop advanced thermal and power management algorithms. In this role, you will collaborate with a cross-functional team to design, implement, and validate algorithms that power millions of Apple devices worldwide.

Description

In this role, you will design, implement, debug, and validate control and estimation algorithms for complex thermal and electrical systems. You'll work closely with electrical and thermal engineering teams to interpret system requirements and constraints, and partner with software engineering teams to ensure that control algorithms are integrated in a robust, scalable, and efficient manner.

You will design and execute experiments for modeling and validation, collect and analyze data, and identify potential issues. When challenges arise, you'll be expected to propose thoughtful fixes and architectural decisions to ensure system performance and reliability.

This role offers a unique opportunity to work across hardware and software domains and to contribute directly to the performance of Apple's world-class products.

Minimum Qualifications

BS in Electrical Engineering, Mechanical Engineering, Aerospace Engineering, Robotics, Computer Science or similar degree.
Hands-on experience in control systems development. (Such as modeling, algorithm design, simulation, implementation and/or testing)
Experience in Python or MATLAB.
Experience implementing control algorithms on embedded microcontroller platforms.
Experience with optimization techniques and modern control theory.

Preferred Qualifications

3 years relevant industry experience.
M.S. or Ph.D. in Electrical Engineering, Mechanical Engineering, Aerospace Engineering, Robotics, or Computer Science, with a focus on control systems or robotics, or equivalent professional experience.
Proficiency in C++.
Experience with software engineering workflows, including Git, code review, and CI/CD pipelines.
Strong knowledge of system identification, estimation theory, and statistical learning methods.
Knowledge of optimal and robust control, adaptive control, model predictive control and/or task and trajectory planning.
Ability to communicate complex control and algorithmic concepts clearly to cross-functional hardware and software teams.