Analyze GPU workloads performance and bottlenecks various devices. Implement and/or suggest improvements to remove the identified bottlenecks.

Build targeted microbenchmarks to help understand strengths and weaknesses of various GPUs and usage patterns.

Guide the development of forward looking GPU workloads to best represent where the industry is headed.

Help improve Apple products by identifying areas of improvements at the GPU architecture and implementation, driver, compiler and API level.

Minimum Qualifications
Bachelor’s degree or equivalent job-related experience in Computer Engineering, Computer Science, or a related field
20+ years of work experience in GPU software performance optimization
Knowledge of computer architecture fundamentals
Background in software engineering, performance analysis tools, methods, and the performance optimization process
Experience and proficiency in some of the C/C++ family programming languages, and scripting languages such as Python
Experience and proficiency with all popular high level graphics APIs
Experience in software development for GPUs
Experience with AI, graphics, or other GPU performance benchmarks and workloads

Preferred Qualifications
Someone who views performance problems as a challenge, a puzzle to solve
Experience with GPU performance tools
Experience profiling GPU workloads to understand performance issues
System wide understanding of data and command flow: from developer to silicon and the layers in between including high level graphics APIs, driver, firmware, compiler down to the GPU hardware implementation
Ability to prototype and benchmark algorithms on GPU,, analyze performance metrics, and create high-level complexity models
Knowledge of operating system internals and compiler technologies
Technical aptitude and curiosity. Ability to collaborate effectively with team members, partners, and stakeholders