GPU Architect, Platform Architecture
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Description
The Platform Architecture GPU group is looking for a talented GPU Architect to join the Neural Accelerator effort with strong skills in performance analysis and development at the level of ML frameworks and lower-level kernel implementations.
Responsibilities
- Analyze the performance of linear algebra and machine learning algorithms on Apple GPU platforms, pursuing investigations wherever they take you in Apple software.
- With our partner teams in Software Engineering and Hardware Technologies, formulate system-level strategies to address performance problems and unlock the next level of AI performance for our users.
- Work closely with MLX, MPS and CoreML teams on real ML use-cases in an end-to-end co-design effort, from early design exploration up to product launch.
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Minimum Qualifications
- BS degree
- Experience with software and hardware performance analysis and optimization
- Experience in GPU programming models such as Metal, CUDA, or similar
- Experience with ML frameworks, for example MLX, Pytorch, or similar
Preferred Qualifications
- MS or PhD in Computer Science, Electrical Engineering, or equivalent
- 20+ years of relevant industry experience
- Experience working specifically in CUDA C++ on ML and/or linear algebra algorithms
- Experience optimizing LLM inference for low latency at the implementation level
- Experience optimizing LLM inference at scale in the cloud or datacenter
- Ability to communicate across both hardware and software organizations
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