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Co-op Researcher-Computer Vision and Machine Learning
Co-op Researcher-Computer Vision and Machine LearningHuawei Technologies Canada Co., Ltd. • Markham, York Region, CA
Co-op Researcher-Computer Vision and Machine Learning

Co-op Researcher-Computer Vision and Machine Learning

Huawei Technologies Canada Co., Ltd. • Markham, York Region, CA
Il y a 9 jours
Type de contrat
  • Temps plein
Description de poste

Huawei Canada Co-op Opening – Assistant Researcher

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 videos and image analysis using cutting‑edge deep learning and computer vision techniques.
  • Take into consideration of the mobile computing constraints for the optimization of algorithms and machine learning models.

About the ideal candidate :

  • Currently enrolled in Bachelor or Mater program in Computer Science, Electrical Engineering or a related technical field, having strong software development skills, previous internship experiences with C++ and Python development.
  • Solid understanding of computer science fundamentals (Data Structure / Algorithm).
  • Good understanding of machine learning techniques (Regression / SVM / PCA / neural networks, etc.).
  • Experience with applying machine learning or computer vision to real‑world problems.
  • Coding language : Python and libraries such as numpy, matplotlib, scikit‑learn. Deep learning frameworks (at least one) : TensorFlow, PyTorch, etc.
  • Experience with image processing libraries (e.g. OpenCV and ffmpeg) and softwares (e.g. Adobe Photoshop) is an asset.
  • Experience with AIGC tools (e.g., Stable Diffusion, Flux, plugins like ControlNet) is an asset.
  • Experience with deploying neural networks on edge devices, Android development, and JNI, is an asset.

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