Microsoft Principal Software Engineer 

United States, Washington 

641690003

Required Qualifications:

• Bachelor's Degree in Computer Science, or related technical discipline AND 6+ years technical engineering experience with coding inC, C++ or Python
  • OR equivalent work experience.
• 1+ yearsexperience working on real-world applications that use CUDA, including experience optimizing CUDA kernels for performance.
• 1+ yearsexperience with parallel algorithms for communication between GPUs and familiarity with related libraries and frameworks (i.e. DeepSpeed, PyTorch Distributed, Horovod, Megatron, MSCCL, NCCL).

Other Qualifications:

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:

• 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
• Experience with OSS, Docker, Kubernetes
• Experience with Python, GOLANG, Rust programming languages
• Knowledge of LLM/Diffusion model architectures (e.g. GPT, Stable Diffusion)
• Experience in distributed computing and architecture.
• Experience in developing low latency systems.
• Experience in developing and operating high scale, reliable online services.
• Experience working in a geo-distributed team

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until July 04, 2024.

• Engage directly with key partners to understand and implement complex inferencing capabilities for state-of-the-art LLMs and Diffusion models.
• Work with cutting edge hardware stacks and a fast-moving software stack to deliver best of class inference and optimal cost.
• Anticipate, identify, assess, track, and mitigate project risks and issues in a fast-paced start up like environment.
• Motivated to build constructive and effective relationships and solve problems collaboratively.
• Support production inference SLAs for core AI scenarios on one of the largest GPU fleets in the world