Microsoft Software Engineer II GPU Performance 

United States, Washington 

703141003

This is a technical role focused on performance analysis and optimization of machine learning models: it requires hands-on software development skills. We’re looking for someone who has a demonstrated history of solving hard technical problems and is motivated to tackle the hardest problems in building a full end-to-end AI stack. An entrepreneurial approach and ability to take initiative and move fast are essential.

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

• Software development in C/C++, Python, and in GPU languages such as CUDA, ROCm, or Triton
• Work with cutting-edge hardware stacks and a fast-moving software stack to deliver best-of-class inference and optimal cost.
• Engage with key partners to understand and implement performance analysis and optimization for state-of-the-art LLMs and other models.
• Embody our and