Senior Deep Learning Performance Architect
| Company | NVIDIA |
|---|---|
| Location | Redmond, WA, USA, Santa Clara, CA, USA |
| Salary | $184000 – $356500 |
| Type | Full-Time |
| Degrees | Master’s, PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- MS or PhD in Computer Science, Computer Engineering, Electrical Engineering or equivalent experience
- 6+ years of meaningful work experience
- Strong background in GPU or Deep Learning ASIC architecture for training and/or inference
- Experience with performance modeling, architecture simulation, profiling, and analysis
- Solid foundation in machine learning and deep learning
- Strong programming skills in Python, C, C++
Responsibilities
- Develop innovative architectures to extend the state of the art in deep learning performance and efficiency
- Analyze performance, cost and power trade-offs by developing analytical models, simulators and test suites
- Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications
- Develop, analyze, and harness groundbreaking Deep Learning frameworks, libraries, and compilers
- Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW
Preferred Qualifications
- Background with deep neural network training, inference and optimization in leading frameworks (e.g. Pytorch, JAX, TensorRT)
- Experience with relevant libraries, compilers, and languages – CUDNN, CUBLAS, CUTLASS, MLIR, Triton, CUDA, OpenCL
- Experience with the architecture of or workload analysis on other DL accelerators
- Demonstration of self-motivation, with a knack for critical thinking and thinking outside the box