Machine Learning Researcher -LLM Agents & Efficient Deep Learning

Reposted One Month Ago
Be an Early Applicant
Montréal, QC, CAN
In-Office
106K-156K Annually
Mid level
Information Technology • Other
The Role
The role involves developing efficient methods for deep learning, optimizing performance of ML systems, and prototyping new ideas. Candidates should have a strong background in AI research and production settings.
Summary Generated by Built In
Huawei Canada has an immediate 12months opening for a Machine Learning Researcher.About the Team:

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.

About the Job:
  • 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 (e.g., 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; 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 (e.g., 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.

Additional Information

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.

Skills Required

  • MSc or PhD in Computer Science, Electrical Engineering, or related field
  • Strong publication record in top AI conferences
  • Strong background in deep learning and optimization
  • Experience with transformer architectures, LLM, SLM
  • Proficiency in Pytorch
  • Solid understanding of linear algebra and probability
  • Experience implementing ML systems in production or research settings
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The Company
HQ: Sham Chun Hu
1,770 Employees
Year Founded: 1987

What We Do

Founded in 1987, Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. We are committed to bringing digital to every person, home and organization for a fully connected, intelligent world. We have approximately 197,000 employees and we operate in over 170 countries and regions, serving more than three billion people around the world. In Canada, Huawei conducts innovative and leading edge research in 5G technologies, along with advanced development of emerging cloud, device and network technologies & services. While our renowned Canada Research Centre in the thriving technology landscape of Ottawa, Ontario continues to grow rapidly in size and strategic product initiatives, additional presence has also been established across Canada with R&D facilities in Vancouver, Edmonton, Waterloo, Markham, Montreal, and a R&D office in Quebec City.

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