Apple’s Server ML Frameworks team in GPU, Graphics and Machine Learning works on enabling Apple Intelligence through high-performance, distributed inference of GenAI applications (such as LLMs) on Private Cloud Compute. You will get to work on custom-built server hardware that brings the power and security of Apple silicon to the data center. We are looking for engineers with systems background who are deeply passionate about building scalable, efficient, and production-grade solutions tailored for high-throughput GPU execution.

Description

Our team is seeking extraordinary machine learning and GPU programming engineers who are passionate about providing robust compute solutions for accelerating Machine learning libraries on Apple Silicon. Role has the opportunity to influence the design of compute and programming models in next generation GPU architectures.

Minimum Qualifications

• 3+ years of programming and problem-solving experience with C/C++/ObjC
• Experience with GPU kernel development & optimizations using compute programming models such as Metal, CUDA etc.
• Experience with Distributed training or inference techniques
• Experience with system level programming and computer architecture

Preferred Qualifications

• Experience with graph compilers such as CuTE, CuTile, Triton, OpenXLA or LLVM is a plus
• Good understanding of LLM and Diffusion based model architectures