Advance large language model efficiency with Huawei Canada as a Researcher intern, applying Python and PyTorch to scalable architectures. Work in Quebec’s French-speaking setting.
Within Huawei Canada’s Noah’s Ark lab, this internship supports research on efficient and scalable LLMs. You will explore long-context models, data curation, and post-training methods. The work connects experiments, analysis, presentations, and publications in machine learning and NLP.
Key Responsibilities: Propose and explore ideas improving LLM efficiency and scalability
Contribute to long-context LLM research projects
Design experiments and analyze research results
Present findings across end-to-end research projects




Publish research in machine learning and NLP conferences
Requirements: Pursuing a Ph.D. or Master’s in computer science or related field
Understand NLP, LLM fundamentals, and machine learning theory
Know transformer and linear-attention model architectures
Program in Python and use PyTorch for LLM work
Communicate effectively in English and collaborate in research settings
Apply LLM architecture, PyTorch, experimentation, and NLP research skills to Huawei Canada’s efficiency-focused projects.

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📌 LLM Efficiency Research Intern (Ontario)
🏢 Huawei Technologies Canada Co.
📍 Ontario