Overview
Work across multiple layers of the AI software stack (abstractions, programming models, compilers, runtimes, libraries, and APIs) to enable large-scale model training and inference. Debug, profile, and optimize performance for training/inference workloads on Central Processing Units (CPUs)/Graphics Processing Units (GPUs). Monitor performance regressions and drive continuous improvements to reduce time-to-deploy and hardware footprint. Collaborate across teams of researchers and engineers to deliver scalable, production-ready AI performance improvements 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++, or Python OR equivalent experience. Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in language
Full job description
Full Job Description
Work across multiple layers of the AI software stack (abstractions, programming models, compilers, runtimes, libraries, and APIs) to enable large-scale model training and inference. Debug, profile, and optimize performance for training/inference workloads on Central Processing Units (CPUs)/Graphics Processing Units (GPUs). Monitor performance regressions and drive continuous improvements to reduce time-to-deploy and hardware footprint. Collaborate across teams of researchers and engineers to deliver scalable, production-ready AI performance improvements 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++, or Python OR equivalent experience. Master'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++, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C++, or Python OR equivalent experience. 4+ years' practical experience working on high performance applications and performance debugging and optimization on CPUs/GPUs. 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 and HPC applications, including proficiency using GPU profiling tools. Cross-team collaboration skills and the desire to collaborate in a team of researchers and developers. Ability to independently lead projects
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