Machine Learning Researcher Llm Efficiency

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 pipelinesDevelop quantization, pruning, sparsity, and decomposition methodsExplore LoRA and memory-efficient long-context modelingOptimize latency, throughput, and KV-cache efficiencyIntegrate reasoning models with function-calling frameworksRequirements:
MSc or PhD in computer science, electrical engineering, or related fieldStrong deep learning and optimization backgroundExperience with transformer architectures, LLMs, and SLMsProficiency in PyTorchStrong publication record in top AI conferencesApply research expertise in PyTorch, optimization, and efficient inference to Huawei Canada’s LLM and SLM development.
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