Apple Neural Engine Performance and Power Engineer
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One of tech's least standardized loops: you interview for a specific team, and every stage belongs to it. Recruiter/hiring-manager screen, one to three 45–60 minute Coderpad coding screens, a system design round shaped by Apple's reliability and privacy constraints, and a behavioral round — then a panel debrief. There is no central question bank; questions map to the team's real stack.
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Summary
At the core of Apple Intelligence revolution lies the groundbreaking Apple Neural Engine. This proprietary hardware accelerator is the key to unlocking real-time, energy-efficient, and high-performance execution of Generative AI models right on your device. As a Performance and Power Engineer in the Apple Neural Engine Software team, you will design and implement novel solutions to help optimize performance and energy efficiency for the AI workloads of tomorrow. This role is an opportunity to leave an enduring mark on the world of technology, having a direct positive impact on millions of Apple customers worldwide.Description
In this highly visible and influential Performance and Power Engineer role within the Apple Neural Engine Software team, you will be expected to: - Analyze and optimize end-to-end system performance of artificial intelligence applications across a wide range of Apple product platforms - Identify and resolve performance bottlenecks across software and hardware architecture - Collaborate with cross-functional Apple teams including AI/ML, Software and Hardware to design and implement performant solutions - Conduct performance profiling, monitoring and diagnostics using and developing specialized tools - Engage with QA teams to craft performance and power tests on AI workloadsMinimum Qualifications
BS and a minimum of 10 years experience with system performance analysis Excellent programming skills in C or PythonPreferred Qualifications
MS or PhD in computer science, machine learning or related field Experience in performance or power architecture, modeling or validation Familiarity with AI networks for example CNN, transformer and diffusion model architectures and their performance characteristics Proficiency with profiling and optimizing complex software Experience with distributed computing or hardware acceleration Strong background in data science and statistical methods, with demonstrated ability to analyze large datasets and present complex insights clearly Experience with data visualization tools (e.g., Tableau) is desirable Experience with C++/Swift/Objective-C Strong written and verbal communication skillsMore engineering roles at Apple
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