Intern Researcher - LLMs/Intelligent system

Huawei Canada has an immediate 4-month Internship opening for a Researcher.

About the team:

The Intelligent Testing Technology Team, currently a part of the Waterloo Research Centre, is at the forefront of integrating large language models (LLMs) with formal methods to advance artificial intelligence. By harnessing LLMs' strengths in natural language processing and generation, this team explores their synergy with the precision of formal verification techniques. As part of this team, you will collaborate with industry leaders on groundbreaking projects and contribute to shaping the future of technology.

About the job:

• Conduct research and development in the area of LLM-based intelligent systems, focusing on multi-agent collaboration, context engineering, and self-healing mechanisms

• Design and implement AI-driven workflows using tools such as LangGraph, LangChain, or similar orchestration frameworks for building complex, reasoning-capable agent systems

• Explore function calling, dynamic context management, and tool-use strategies to enhance adaptability and decision-making in large-scale AI systems

• Collaborate with researchers in AI, software engineering, and systems verification to prototype next-generation intelligent software systems.

• Contribute to internal reports, publications, and proof-of-concept demos showcasing the application of LLMs to automated reasoning, testing, and system optimization

• Remain **flexible and open to gaining new domain knowledge as research directions evolve

About the ideal candidate:

• Currently pursuing a Master’s or PhD in Computer Science, Software Engineering, Artificial Intelligence, or a related field

• Hands-on experience with LLM frameworks (e.g., LangGraph, LangChain, OpenAI, Gemini, or Hugging Face)

• Understanding of multi-agent system design, context engineering, and function calling in LLM applications

• Strong programming skills in Python and familiarity with prompt engineering and retrieval-augmented generation (RAG)

• Knowledge of autonomous system design, self-healing systems*, or AI orchestration pipelines is an asset

• Demonstrated ability to adapt to new problem domains and learn emerging AI concepts quickly

• Ability to work in a collaborative, research-oriented environment and contribute to advancing intelligent, adaptive software systems