GPU Compiler Performance Engineer – GPU ASICS Engineering
| Company | Qualcomm |
|---|---|
| Location | Markham, ON, Canada |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Mid Level, Senior |
Requirements
- Bachelor’s degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 4+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
- Master’s degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 3+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
- PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
Responsibilities
- Profile and characterize trending GPU benchmarks and applications (games, HPC, AR/VR and AI)
- Use/develop tools to identify performance bottlenecks and study optimization heuristics
- Propose/prototype improvements in compilers and GPU architecture to tackle identified bottlenecks
- Provide programming guide to help developers get better performance on Qualcomm GPUs
- Leverages advanced GPU knowledge and experience to architect, design, implement, verify, and/or optimize the performance and power of GPU cores.
- Builds functional model simulations, develops software, and tests for various graphics to verify correctness and ensures advanced performance and power goals are met.
- Designs, programs, and runs comprehensive graphics tests using tools and methods under different scenarios and benchmarks to verify functionality, performance, power, and stability and identify issues.
- Collaborates with cross-functional teams, third-party vendors, and external users to guide implementation and ensure alignment with needs and goals.
- Develops critical driver and compiler software to support GPU products.
- Writes detailed technical documentation and feature descriptions for complex GPU projects to guide users and/or customers to implement output.
Preferred Qualifications
- Broad compiler knowledge, development, and optimization experience
- Deep understanding of computer architecture (GPU, memory, data layout, etc.) and performance tradeoffs
- Understanding of parallel computing on multi-core CPU, GPU, or heterogeneous systems
- Extensive experience with benchmarking and performance analysis and tuning for parallel applications
- Good communication skills and teamwork spirit, reliable and self-motivated
- Graphics shader programming (OpenGL, Vulkan, DirectX, or others) or OpenCL/CUDA/SYCL kernel development
- Experience with performance profiling and modeling for games, HPC, AR/VR, or AI applications
- Experience with machine learning / deep learning tools (scikit learn, tensorflow, or others)