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Huawei Canada has an immediate internship opening for a LLMs 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

• Research and develop next-generation AI agents powered by large language models for autonomous reasoning, planning, and task execution
• Prototype and evaluate core agent capabilities such as memory, tool use, self-reflection, retrieval, and long-horizon decision-making
• Build and experiment with multi-agent systems for collaboration, coordination, and complex problem solving
• Integrate AI agents with external tools, APIs, and real-world environments to enable intelligent automation workflows
• Explore emerging research directions in reasoning-enhanced LLMs, agent alignment, world models, and embodied intelligence
• Conduct experiments, analyze results, and iterate rapidly on new research ideas and prototypes
• Collaborate closely with researchers and engineers to translate cutting-edge research into scalable AI systems
• Contribute to technical reports, publications, demos, and open research initiatives

The total target annual compensation for this position ranges from $58,000 to $104,000 depending on education, experience, and demonstrated expertise.

About the ideal candidate

• Currently pursuing a Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Robotics, or related fields
• Strong background in large language models, AI agents, reinforcement learning, or decision-making systems
• Proven research record in AI by having at least one paper as the first author in top tier venues, such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA.
• Hands-on experience with Python, PyTorch, and modern ML research workflows
• Familiarity with agent architectures, including planning, retrieval, tool use, memory, or multi-agent systems
• Experience building research prototypes and running experiments independently
• Experience working with large-scale datasets, sensor data, transformer-based architectures, or diffusion models is an asset.