5-7 years of experience in AI research or related fields
Deep understanding of large language models (LLMs) and their functionalities
Proven experience in developing or assessing AI agents that interact with web technologies
Proficiency in using AI-assisted coding tools for independent prototyping
Strong research and writing skills for hypothesis formulation and structured communication
Responsibilities
Research interactions between web agents and real-world websites to identify issues
Analyze the impact of various web tech stacks on agent performance
Explore LLMs' understanding of web content and effective representations
Prototype new architectures and interaction models for AI-driven agents
Test hypotheses to enhance web capabilities with AI agents
Benefits
Immediate permanent position with a leading tech company
Opportunity to work on cutting-edge AI and web technologies
Collaborative environment with a focus on innovation
Access to professional development resources
Potential for career growth within a global organization
Full Job Description
Huawei Canada has an immediate permanent opening for a Researcher.
About the job:
Research how state-of-the-art web agents (browser-use, computer-use, MCP-based agents) interact with real-world websites - identifying failure modes, reliability gaps, and capability ceilings.
Study how different web tech stacks affect agent performance, and define design patterns that make sites more agent-friendly.
Investigate how LLMs perceive and reason about web content (HTML, rendered DOM, screenshots, accessibility trees) and which representations are most effective for different tasks.
Prototype new architectures, interaction models, and agent frameworks to empirically test hypotheses and bridge Web capabilities with AI-driven Agents.
The total target annual compensation (based on 2,080 hours per year) ranges from $106,000 to $156,000 depending on education, experience, and demonstrated expertise.
About the ideal candidate:
Solid understanding of how LLMs work - including prompting, context management, tool use, and reasoning patterns.
Hands-on experience building or evaluating AI agents - particularly those that interact with external environments (web, APIs, tools).
Comfortable using AI-assisted coding tools to build and iterate on prototypes independently; able to build prototypes independently.
Strong research and writing skills, able to formulate clear hypotheses, design experiments, and communicate findings in structured written form.
