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Huawei Canada in Markham is offering an 8/12/16-month Co-op opening for an Assistant Researcher in AI and computer vision. You will contribute to state-of-the-art ML research and mobile deployment optimizations.
The ideal candidate is a senior undergrad or master's student in CS/EE with strong C++ and Python skills, experience in TensorFlow or PyTorch, and a passion for AI research with real-world impact.
Huawei Canada has an immediate 8/12/16-month Co-op opening for an Assistant Researcher.
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.
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.
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 andfamiliar 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.