Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent practical experience.
3 years of experience with GPU microarchitecture memory sub-system and scheduling mechanisms.
Experience with programming languages such as C, C++, or Python.
Preferred qualifications:
Master’s degree in Electrical Engineering, Computer Engineering, or Computer Science, emphasizing on computer architecture.
Understanding of system-level interactions between the GPU, CPU, memory and other components, including knowledge of interconnect.
Deep understanding of processor design principles, pipeline optimization, memory hierarchies, Instruction Set Architectures (ISA), and microarchitecture concepts.
Familiarity with operating system concepts like memory management, scheduling and device drivers, especially for GPU drivers.
Familiarity with tools to generate thread level parallelism reports.
Proficiency in profiling tools and techniques to identify bottlenecks and optimize GPU performance.