Machine Learning Researcher -LLM Agents & Efficient Deep Learning

Position Summary

Huawei Canada has an immediate 12‑month opening for a Machine Learning Researcher.

Founded in 2012, the Noah’s Ark lab has evolved into a prominent research organization with notable achievements in academia and industry. The lab’s mission focuses on advancing artificial intelligence and related fields to benefit the company and society. Driven by impactful, long‑term projects, the aim is to enhance state‑of‑the‑art research while integrating innovations into the company's products and services, including LLMs, RL, NLP, computer vision, AI theory, and autonomous driving.

• Multi‑agent systems and function call models. Build scalable SLM pipelines for training, evaluation, and deployment.
• Develop methods for efficient training and inference, including quantization (low‑precision formats, INT8/FP8), pruning and sparsity, low‑rank and tensor decompositions.
• Explore advances in parameter‑efficient fine‑tuning such as LoRA, memory and long‑context modeling, and adapt GPU‑based LLMs for CPU‑based SLMs.
• Prototype new ideas and validate them through rigorous experimentation.
• Optimize inference performance (latency, throughput, KV‑cache efficiency).
• Integrate reasoning models with tool‑use frameworks (function calling, APIs).

The total target annual compensation for this position ranges from $106,000 to $156,000 depending on education, experience, and demonstrated expertise.

• MSc or PhD in Computer Science, Electrical Engineering, or related field.
• Strong publication record in top AI conferences such as NeurIPS, ICML, AAAI, ICLR, etc.
• Strong background in deep learning and optimization.
• Experience with transformer architectures, LLM, SLM.
• Proficiency in PyTorch.
• Solid understanding of linear algebra and probability; optimization algorithms (SGD, Adam, etc.).
• Experience implementing and scaling ML systems in production or research settings.

Huawei Canada is committed to a fair, inclusive, and accessible recruitment process. If you require accommodation during any stage of the hiring process, please let us know and we will work with you to meet your needs.

All applications for this position are reviewed directly by our hiring team. We do not use artificial intelligence tools to screen or select candidates.