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.
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.\n\nYou 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.\n\nThis 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.
BS in Electrical Engineering, Mechanical Engineering, Aerospace Engineering, Robotics, Computer Science or similar degree.\nHands-on experience in control systems development. (Such as modeling, algorithm design, simulation, implementation and/or testing)\nExperience in Python or MATLAB.\nExperience implementing control algorithms on embedded microcontroller platforms.\nExperience with optimization techniques and modern control theory.
10 years relevant industry experience.\nM.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.\nProficiency in C++.\nExperience with software engineering workflows, including Git, code review, and CI/CD pipelines.\nStrong knowledge of system identification, estimation theory, and statistical learning methods.\nKnowledge of optimal and robust control, adaptive control, model predictive control and/or task and trajectory planning.\nAbility to communicate complex control and algorithmic concepts clearly to cross-functional hardware and software teams.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: aea402e358755050e0062aeef6ce18c
- Posted 9 hours ago
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