Intern - Researcher

Job summary

Design and implement advanced reinforcement learning models for large-scale graph-structured optimization and complex scheduling problems. Collaborate with researchers to prototype and integrate AI research ideas into proof-of-concept systems.

Job details

Huawei Canada has an immediate co-op opening for an Intern. About the team: Welcome to the Advanced Wireless Technology Wireless Lab, an epitome of innovation located in Ottawa, Canada. Here, amid the dynamic panorama of technological progress, our team consists mainly of seasoned graduate computer engineers and computer scientists. With diverse experiences ranging from fresh perspectives to decades-long industry immersion, we are united by our fervour for pioneering wireless solutions. About the job: * Design and implement advanced reinforcement learning for large-scale graph-structured optimization and complex scheduling problems. * Enabling Large Language Models (LLMs) to learn from experience, interaction, and environment feedback, moving beyond static fine-tuning toward continual, agentic self-improvement. * Collaborate closely with researchers to prototype, implement, and integrate research ideas into proof-of-concept. * Stay current with literature and recent advances in the AI domain for high-performance computing. * Contribute to scientific papers. The total targeted 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 ideal candidate: * Currently pursing a PhD degree or master's degree in Computer Science or related fields. * Background in machine learning, deep learning and practical or research experience in reinforcement learning, self-supervised learning, or language model fine-tuning. * Strong theoretical in advanced reinforcement learning (agentic RL, multi-agent RL or Meta-RL). * Familiarity with LLMs or generative AI methods and their integrations into structured reasoning or decision systems. * Excellent communication skills, self-motivated, with creative thinking and attention to details. 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.

What you’ll do

Design and implement advanced reinforcement learning models for large-scale graph-structured optimization and complex scheduling problems. Collaborate with researchers to prototype and integrate AI research ideas into proof-of-concept systems.

Requirements

Candidates must be currently pursuing a PhD or master's degree in Computer Science or a related field. A strong background in machine learning, deep learning, and reinforcement learning is required.

Listed skills

• Communication · Preferred
• scheduling · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Reinforcement learning
• Deep learning
• Large language models
• Graph-structured optimization
• Scheduling
• Agentic RL
• Multi-agent RL
• Meta-RL
• Self-supervised learning
• Generative AI
• Structured reasoning
• Decision systems
• High-performance computing
• Prototyping
• Research
• Communication
• Large Language Modeling
• Fine-tuning (Deep Learning)
• Generative Artificial Intelligence
• Language Models
• Self-Motivation
• Meta-Reinforcement Learning
• Multi-Agent Systems
• Artificial Intelligence
• Computer Science
• Computer Engineering
• Creative Thinking
• Innovation
• Machine Learning
• Research Experiences
• Supervised Learning
• Reinforcement Learning
• Deep Learning
• Detail Oriented

Job areas

• Technology
• Science & Research
• Software
• Data & Analytics
• Engineering
• Research Assistant Co-Op
• Natural Language Processing Engineer
• Software Developers
• Computer and Information Research Scientists

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