Technical VP - Computing Bus System Research
Markham, ONHuawei Technologies Canada Co., Ltd.
Candidates need strong computer science and computer architecture knowledge, including bus and network protocols such as PCIe, CXL and InfiniBand. Experience designing architectures for high-bandwidth, low-latency interconnects, leading chip or product development, and technical leadership are required.
Research, Data analysis, Decision making, Computer science, Architectural design, Leadership
Principal Architect – Hardware Efficient AI Foundation Model Training
Markham, ONHuawei Technologies Canada Co., Ltd.
Candidates need experience training and deploying AI models of 10B+ parameters, knowledge of the latest AI architectures and frameworks such as PyTorch and vLLM, and understanding of AI chip architecture. A PhD is preferred, and publications in AI systems or chip design are an asset.
PyTorch, vLLM, SGLang, GPU, NPU, TPU
Senior Researcher – Hardware Efficient AI Foundation Model Training
Markham, ONHuawei Technologies Canada Co., Ltd.
Candidates need experience training and deploying AI models of 10B+ parameters, knowledge of modern AI architectures such as long-sequence, reinforcement learning, multimodal and agent models, and solid command of AI frameworks and distributed training. Familiarity with AI chip architectures (GPU, NPU, TPU) is an asset, and a PhD and publications in AI systems or chip design are assets.
PyTorch, vLLM, SGLang, GPU, NPU, TPU
Intern Researcher – AI Foundation Model Training
Markham, ONHuawei Technologies Canada Co., Ltd.
Candidates need to be currently pursuing a PhD or Master's degree in computer science, electrical engineering or a related field. Familiarity with deep learning frameworks such as PyTorch and distributed training concepts is needed, with GPU or accelerator experience and research or open-source contributions as assets.
PyTorch, vLLM, SGLang, GPU, NPU, TPU
Research Engineer - AI Workload & Systems
Markham, ONHuawei Technologies Canada Co., Ltd.
Candidates need a strong understanding of modern AI architectures and AI accelerator hardware such as GPUs and TPUs. Hands-on kernel development experience with CUDA or Triton, plus LLM inference and profiling experience, is required; a PhD is an asset.
CUDA, Triton, TileLang, vLLM, SGLang, PyTorch