Microsoft's AI Frameworks team is developing AI software to run AI models efficiently across various devices, from supercomputers to IoT devices and browsers. They are focused on optimizing the inference performance of large language models (LLMs) like those from OpenAI, serving massive workloads for Microsoft products and aiming to reduce hardware costs for Azure AI.
Requirements
- coding in languages including, but not limited to C/C++, Python
- 4+ years’ practical experience working on high performance applications and performance debugging and optimization on CPU's/GPU's
- Experience in DNN/LLM inference and experience in one or more DL frameworks such as PyTorch, Tensorflow, or ONNX Runtime and familiarity with CUDA, ROCm, Triton
- Technical background and solid foundation in software engineering principles, computer architecture, GPU architecture, hardware neural net acceleration
- Experience in end-to-end performance analysis and optimization of state of the art LLMs, HPC applications including proficiency using GPU profiling tools
Responsibilities
- Identify and drive improvements to end-to-end inference performance of OpenAI and other state of the art LLMs
- Measure, benchmark performance on Nvidia/AMD GPU's and first party Microsoft silicon
- Optimize and monitor performance of LLMs and build software tooling to enable insights into performance opportunities ranging from the model level to the systems and silicon level, help reduce the footprint of the computing fleet and achieve Azure AI capex goals
- Enable fast time to market of LLMs/models and their deployments at scale by building software tools that afford velocity in porting models on new Nvidia, AMD GPUs and Maia silicon
- Design, implement, and test functions or components for our AI/deep neural networks (DNN)/LLM frameworks and tools
- Speeding up/reducing complexity of key components/pipelines to improve performance and/or efficiency of our systems
- Communicate and collaborate with our partners both internal and external
Other
- Embody Microsoft's Culture and Values
- Cross-team collaboration skills and the desire to collaborate in a team of researchers and developers
- Ability to independently lead projects
- An entrepreneurial approach and ability to take initiative and move fast are essential.
