About the role
As a Principal Software Engineer on
the team the common tasks of the job would include, but not be limited to: Identify and drive improvements to end-to-end inference performance of OpenAI and other state of the art LLMs Optimize and monitor performance of LLMs and build SW 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 SW 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/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 Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Master's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 15+ 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' practical experience working on high performance applications and performance debug and optimization on CPU's/GPU's. Technical background and solid foundation in software engineering principles, computer architecture, GPU architecture, HW 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. 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.
