GPU ML Engineer at Apple in Cupertino, CA

Apple’s Compute Frameworks team in GPU, Graphics and Displays org provides a suite of high-performance data parallel algorithms for developers inside and outside of Apple for iOS, macOS and Apple TV. Our efforts are currently focused in the key areas of linear algebra, image processing, machine learning, along with other projects of key interest to Apple. We are always looking for exceptionally dedicated individuals to grow our outstanding team.

Our team is seeking extraordinary machine learning and GPU programming engineers who are passionate about providing robust compute solutions for accelerating machine learning networks on Apple Silicon.

Role has the opportunity to influence the design of compute and programming models in next generation GPU architectures.

Adding optimized GPU compute kernels across Machine Learning, Image Processing, Linear Algebra and Computer Vision.
Defining and implementing APIs in Metal Performance Shaders.
Performing in-depth analysis, compiler and kernel level optimizations to ensure the best possible performance across hardware families.
Partnering with Platform Architecture teams to define Apple GPU's compute hardware roadmap. Working with hardware team to analyze performance on future silicon
Tune GPU-accelerated compute across products.

Technical BS/MS degree and Equivalent experience.
2 plus years of experience
GPU compute kernel framework development, maintenance, and optimization.
Experience with system level programming and computer architecture.
Experience with high performance parallel programming, GPU programming experience

Excellent programming and problem-solving skills.
Strong communication skills.
Strong collaboration skills.
Good understanding of machine learning fundamentals.
Background in mathematics, including linear algebra and numerical methods is a plus.