Huawei Technologies Canada Co., Ltd.

Intern Research Engineer - AI Agent Systems

Markham, Ontario, Canada · Intern · Internship

Sponsorship not specified$58k-$104kDetected 29 days ago

TypeScriptPythonReactAndroidVector DatabasesLLMsLangGraphResearchCollaboration

About the role

The Technology Planning and Cooperation Department promotes strategic innovation across all of Huawei Canada.
Working with fellow experts, the focus is researching new and upcoming areas of technology as well as strategic planning to help achieve long term vision of Huawei.

Design and optimize advanced memory substrates for Agents, tackling challenges related to long-context handling, state persistence, and execution efficiency.
Deep understanding of Agentic design patterns (Planning, Memory, Tool Use, Multi-Agent Collaboration).

About the ideal candidate: Currently pursuing a Master's or Bachelor's Degree in Computer Science or a highly quantitative field, with a focus on AI, Software Engineering Systems, or Distributed Systems.

Currently pursuing a Master's or Bachelor's Degree in Computer Science or a highly quantitative field, with a focus on AI, Software Engineering Systems, or Distributed Systems.
Proficient in orchestrating LLMs programmatically.
Deep experience with frameworks such as LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or building custom agentic runtime systems.
Experience with Code-LLM optimization (e.g., custom fine-tuning for code generation, structured outputs), embedded database engines or high-performance vector stores is an asset.

Huawei Canada is committed to a fair, inclusive, and accessible recruitment process.
This department offers a unique opportunity to leverage both technical and business skills.
Exceptional coding skills in Python and/or TypeScript/ Node.js.
Contributions to open-source AI Agent frameworks, developer tools, or compiler-related projects is an asset.

Architect and implement high-scalability AI Agent pipelines, transforming complex requirements into reliable execution structures (e.g., TaskGraph IR, Operator DAGs, and multi-agent coordination frameworks).
Develop and optimize automated code generation, reasoning, and self-debugging loops that interact directly with multi-framework environments (e.g., creating bridge layers, compilation pipelines, or automated code refactoring tools).
Design and optimize advanced memory substrates for Agents, tackling challenges related to long-context handling, state persistence, and execution efficiency.
Establish rigorous, automated evaluation frameworks to benchmark Agent execution accuracy, latency, and reliability under non-deterministic LLM behaviors.
Translate the latest research in Agentic workflows (e.g., ReAct, Reflection, Planning, Tool Use) into production-grade, highly performant software libraries.
The total target annual compensation (based on 2,080 hours per year) ranges from $58,000 to $104,000 depending on education, experience, and demonstrated expertise.

About the job: Architect and implement high-scalability AI Agent pipelines, transforming complex requirements into reliable execution structures (e.g., TaskGraph IR, Operator DAGs, and multi-agent coordination frameworks).
Develop and optimize automated code generation, reasoning, and self-debugging loops that interact directly with multi-framework environments (e.g., creating bridge layers, compilation pipelines, or automated code refactoring tools).
Establish rigorous, automated evaluation frameworks to benchmark Agent execution accuracy, latency, and reliability under non-deterministic LLM behaviors.
Translate the latest research in Agentic workflows (e.g., ReAct, Reflection, Planning, Tool Use) into production-grade, highly performant software libraries.
The total target annual compensation (based on 2,080 hours per year) ranges from $58,000 to $104,000 depending on education, experience, and demonstrated expertise.
Familiarity with structural design patterns and engineering clean, maintainable codebases.
Ability to quickly digest, implement, and improve upon cutting-edge ArXiv papers on LLM reasoning and code generation.
Familiarity with cross-framework mobile compilation or bridge layers (e.g., Android/AOSP or hybrid application runtimes) is an asset.

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.

This listing is sourced directly from Huawei Technologies Canada Co., Ltd.'s careers page and normalized into a canonical job model.