Software Engineer II

3 weeks ago

Redmond, Washington, United States Microsoft Corporation Full time

At Microsoft Corporation, we're seeking a talented Software Engineer II to join our AI Frameworks team. As a member of this team, you'll have the opportunity to work on the fundamental abstractions, programming models, runtimes, libraries, and APIs to enable large-scale training and inference of models on novel AI hardware.

This is a technical role focused on performance analysis and optimization of machine learning models. It requires hands-on software development skills and a demonstrated history of solving hard technical problems.

We're looking for someone who 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.

We value differences and different perspectives, and we seek them out and invite them in so we can tap into the collective power of everyone in the company.

Responsibilities:

  • 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

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

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

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