Required Qualifications:
- Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C/C++, CUDA, or ROCm
- OR equivalent experience.
- 1+ years’ practical experience working on applications that use GPUs, experience in optimizing their performance
Preferred Qualifications:
- Bachelor's Degree in Computer Science
- OR related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C/C++, CUDA, or ROCm
- OR Master's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C/C++, CUDA, or ROCm
- OR equivalent experience.
- Experience writing new GPU kernels, going beyond experience of GPU workloads with existing library kernels
- Experience in low-level performance analysis and optimization, including proficiency using GPU profiling tools such as NVIDIA Visual Profiler, and NVIDIA Nsight Compute
- Technical background and solid foundation in software engineering principles and architecture design
- Exposure to Deep Neural Network inference and experience in one or more deep learning frameworks such as PyTorch, Tensorflow, or ONNX Runtime
- Cross-team collaboration skills and the desire to collaborate in a team of researchers and developers
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: