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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.
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
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.
Eeo Content
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
