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Huawei Canada

Co-op Researcher – Computer Vision and Machine Learning

Reposted 3 Days Ago
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In-Office
Burnaby, BC, CAN
Internship
In-Office
Burnaby, BC, CAN
Internship
Assist in research and development of computer vision and machine learning technologies through deep learning and image analysis. Optimize algorithms for mobile deployment and contribute to projects involving image and video analysis.
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Huawei Canada has an immediate 8/12/16-month Co-op opening for an Assistant Researcher.

About the team:

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, AI theory, and Autonomous driving.

About the job:

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

  • Work with various types of image and video analysis, using cutting-edge deep learning and computer vision techniques.

  • Work on optimization of algorithms and machine learning models for deployment on mobile.

About the ideal candidate:

  • Currently enrolled in senior Bachelor or Master’s in Computer Science, Electrical Engineering or a related technical field, having strong software development skills, previous internship experiences with C++ and Python development.

  • Solid knowledge of machine learning and deep learning techniques. Experienced in applying machine learning and computer vision to real-world problems.

  • Experience with TensorFlow, Pytorch, or other deep learning frameworks.

  • Experience with Android development and familiar with JNI is an asset.

  • Excellent verbal and written communication skills, self-motivated, with creative thinking and attention to details. Excellent organization skills under pressure and dynamic priorities, effectiveness in prioritizing tasks.

  • Experience in training, regularization, generalization and evaluation of deep learning models, demonstrated through internships and projects.

  • Experience with and knowledge of at least one deep learning architecture (Transformers, GNN, CNN, GAN, LSTM, VAE, ...).

  • Demonstrated experience with Computer Vision projects in industry.

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