Advance LLM efficiency at Huawei Canada through quantization, pruning, and scalable small language model pipelines. This 12-month opening supports research in Canada. As a Machine Learning Researcher with Noah’s Ark lab, you will investigate efficient deep learning for language models and agents. The work spans multi-agent systems, function call models, transformer architectures, and deployment. You will prototype ideas, validate experiments, and connect research with scalable machine learning systems. Key Responsibilities:
Build scalable SLM training, evaluation, and deployment pipelines Develop quantization, pruning, sparsity, and decomposition methods Explore LoRA and memory-efficient long-context modeling Optimize latency, throughput, and KV-cache efficiency Integrate reasoning models with function-calling frameworks Requirements:
MSc or PhD in computer science, electrical engineering, or related field Strong deep learning and optimization background Experience with transformer architectures, LLMs, and SLMs Proficiency in PyTorch Strong publication record in top AI conferences Apply research expertise in PyTorch, optimization, and efficient inference to Huawei Canada’s LLM and SLM development.
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Machine Learning Researcher LLM Efficiency in Markham employer: Huawei Technologies Canada Co., Ltd.
At Huawei Canada, we pride ourselves on being an exceptional employer that fosters innovation and collaboration in the field of optical communications. Our multicultural work environment encourages mentorship and professional growth, providing employees with unique opportunities to engage in cutting-edge projects while developing their skills. With a commitment to employee well-being and a focus on transformative technology, Huawei Canada is the ideal place for those looking to make a meaningful impact in the industry.
Contact Details:
Huawei Technologies Canada Co., Ltd. Recruitment Team
