Intern Researcher - AI Software Development

Huawei Canada has an immediate internship opening for an Intern Researcher. 

About the team:

The Human-Machine Interaction Lab unites global talents to redefine the relationship between humans and technology. Focused on innovation and user-centered design, the lab strives to advance human-computer interaction research. Our team includes researchers, engineers, and designers collaborating across disciplines to develop novel interactive systems, sensing technologies, wearable and IoT systems, human factors, computer vision, and multimodal interfaces. Through high-impact products and cutting-edge research, we aim to enhance user experiences and interactions with technology.

About the job:

• Rapidly prototype, implement, and reproduce state-of-the-art AI and ML models to support next-generation intelligent products, including smartphones, smart glasses, wearables, and other smart devices.

• Explore innovative ideas through literature review, experimentation, and collaboration with research mentors.

• Evaluate model performance, optimize implementations, and contribute to advancing product-level AI capabilities.

• Present research outcomes and findings to internal teams and collaborate closely with product groups to translate research prototypes into deployable solutions.

About the ideal candidate:

• Currently enrolled in a PhD or Master program in Computer Science, Electrical Engineering, Machine Learning, Artificial Intelligence, or a related field.

• Solid understanding of machine learning fundamentals and hands-on experience in deep learning model development.

• Proficiency in Python and experience with major deep learning frameworks such as PyTorch, TensorFlow, or HuggingFace Transformers.

• Strong implementation and debugging skills, with the ability to quickly reproduce and adapt research models from papers or open-source repositories.

• Proven ability to translate research ideas into working prototypes or demonstrable systems.

• Knowledge or experience in speech and audio processing, voice foundation models, or audio-language models is an asset.

• Track record of research contributions through publications, patents, or open-source projects.

• Familiarity with large-scale data processing, model optimization, and evaluation of generative or multimodal AI systems.