AI/ML Performance Engineer for Silicon

Apple Inc.; Cupertino, Northern (CA, KY); Hybrid; USD 129,000 - 225,000; Full time

Job summary

Apple Inc. in Cupertino seeks an engineer for the Platform Architecture group to analyze AI/ML workloads on Apple Silicon and identify performance bottlenecks across GPU, ANE, and CPU.

You will build microbenchmarks, develop optimized software implementations, and contribute to forward-looking workloads while collaborating with silicon, software, and tools teams to advance performance and efficiency.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Electrical Engineering, or related field (or equivalent practical experience).
• Experience with GPU or parallel programming (Metal, OpenCL, CUDA or similar).
• Experience with profiling/performance analysis tools (Xcode Instruments, VTune, Nsight Compute or equivalent).
• Development experience in Python, C or C++.

Responsibilities

• Profile and analyze AI/ML workloads across Apple Silicon compute engines (GPU, ANE, and CPU) to help identify performance bottlenecks, working alongside senior engineers.
• Build targeted microbenchmarks to characterize strengths, weaknesses, and usage patterns of different devices and workloads.
• Develop and tune optimized implementations of software workloads on Apple Silicon (GPU and CPU), applying the latest instruction sets and frameworks.
• Contribute to the development of forward-looking AI/ML workloads that represent where the industry is headed.
• Partner with system and tools teams to prototype performance experiments and help build performance analysis instruments, libraries, and frameworks.
• Grow toward a system-wide understanding of the stack—from high-level APIs down to the hardware.

Skills

GPU programming

Python

C/C++

Metal

OpenCL/CUDA

Xcode Instruments

Profiling tools

Education

Bachelor's degree in CS/CE/Math/EE

Tools

VTune

Nsight Compute

Job description

Apple Inc. in Cupertino seeks an engineer for the Platform Architecture group to analyze AI/ML workloads on Apple Silicon and identify performance bottlenecks across GPU, ANE, and CPU.

You will build microbenchmarks, develop optimized software implementations, and contribute to forward-looking workloads while collaborating with silicon, software, and tools teams to advance performance and efficiency.