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95015, Cupertino, CA
ML Framework (MetalLM) Engineer, Graphics, Game and ML

ML Framework (MetalLM) Engineer, Graphics, Game and ML

Apple

Posted 2 months ago, valid for 19 days

Cupertino, CA 95015, US

Competitive

Full Time

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Sonic Summary

Apple's Server ML Frameworks team is seeking engineers with a systems background to enable high-performance, distributed inference of GenAI applications on Private Cloud Compute.
The role involves working on custom-built server hardware that leverages the power and security of Apple silicon in the data center.
Candidates should have a minimum of 3 years of programming experience in C/C++/ObjC, along with expertise in GPU kernel development and optimizations.
Experience in distributed training or inference techniques and system-level programming is required, with knowledge of graph compilers considered a plus.
The position offers a competitive salary, though the specific amount is not disclosed in the job description.

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

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