Co-op Researcher - LLMs & Computer Vision

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, audio, speech, AI theory, and Autonomous driving.

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  Research and develop state-of-the-art technology in computer vision and machine learning.

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  Work on various image / video understanding and synthesis tasks using cutting-edge deep learning and computer vision techniques.

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  Explore and develop applications of Large Language Models (LLMs) and Vision-Language Models (VLMs) for multimodal understanding, generation, and intelligent agents.

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  Develop and evaluate LLM/VLM-based solutions, including prompt engineering, model adaptation, and multimodal reasoning.

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  Take into consideration of mobile computing constraints for the optimization of algorithms and machine learning models.

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

• Currently pursuing a Bachelor's, Master's or Ph.D. degree in Computer Science or a related field.

• Experience with applying machine learning or computer vision to real-world problems.

• Able to grasp basic concepts and techniques on computer vision, deep learning, and/or large language models.

• Experience in Python coding and version control (e.g., Git).

• Experience in deep learning frameworks (e.g., PyTorch).

• Academic research experience (for example, participation in paper publishing).

• Familiarity with image/video generation models (e.g., GAN, Stable Diffusion, Flux).

• Familiarity with LLMs, Vision-Language Models (VLMs), or multimodal AI.

• Hands-on experience with fine-tuning and adapting LLMs or VLMs, including supervised fine-tuning (SFT).

• Familiarity with reinforcement learning (RL) for LLMs, including preference optimization or RL-based post-training.

• Familiarity with open-source LLM/VLM ecosystems and models (e.g., Llama, Qwen, Gemma, or similar models).

• Familiarity with agentic workflows.

• Knowledge about photography, OpenCV, photo editing (e.g., Photoshop), and/or computer graphics tools (e.g., Blender).

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.