Microsoft Principal Software Engineer - GPU Performance 

United States, Washington 

698590234

raphics processing unit (GPU)performance analysis and optimization. As a member of this team, you will have the opportunity to work on the fundamental abstractions, programming models, runtimes, libraries andapplication programming interfaces (APIs)to enable large scale training and inferencing of models on novel AI hardware.

This is a technical role: it requires hands on software design and 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/Minimum Qualifications

• Bachelor's Degree in Computer Science, or related technical discipline AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

  • OR equivalent experience.

• 4+ years' experience with C/C++
• 4+ years’ practical experience working on real-world applications that use GPUs, experience in optimizing GPU kernels for performance

Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred/Additional Qualifications

• Bachelors Degree or advanced degree in computer engineering, computer science, or related fields, and 10+ years of software development experience.
• Experience in low-level program behavior, including performance and memory usage, proficiency using profiling tools such as NVIDIA Visual Profiler, nvprof, and NVIDIA Nsight Compute
• Technical background and foundation in software engineering principles, architecture design, and performance analysis
• Intellectual curiosity and passion about learning new technologies
• Exposure to state-of-the art Deep Neural Network training and inference workloads, including research techniques
• Great cross-team collaboration skills and the desire to collaborate in a team of researchers and developers

• Collaborate broadly across multiple disciplines from hardware designers to ML developers
• Engage with key partners to understand and implement robust performance analysis and optimization for state-of-the-artlarge language models (LLMs)and other models.
• Perform software development in C/C++, Python, and GPU development in languages such as CUDA, ROCm, or Triton.
• Identify requirements, scope solutions, estimate work, schedule deliverables.
• Embody our and