GPU Engineer, Platform Architecture
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Description
The Platform Architecture GPU group is looking for a talented GPU Engineer 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.
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
- 3+ 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
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 .
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