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Intern Engineer - AI

Huawei Technologies Canada · Vancouver, British Columbia, Canada · Onsite

Weak hiring record · median 197 days open

4141

Hiring signal

Stale

Open 137 days · How we score

All reasons
  • Open 137 days
  • 88% of this employer's openings are over 60 days old

In its favour

  • Still listed on the employer's own board
  • Publishes a salary range

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Intern Engineer - AI at Huawei Technologies Canada. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

Huawei Canada has an immediate 4-month internship opening for an Intern Engineer.

About the team

Established in 2012, the Central Media Technology Institute (CMTI) is Huawei's center for media technology innovation and engineering, enhancing the technical competitiveness of media products. Sitting within CMTI, the Graphics Technology Lab focuses on research and breakthroughs in photography, audio, video, computer graphics, XR, and codec standards to maintain the company's leadership in media technology. Our R&D team comprises skilled CG algorithm experts, researchers, software architects, and standards specialists dedicated to building core capabilities for an improved graphics experience.

About the job

  • Conduct advanced research and engineering on VFX generation, procedural Shape/Texture/VFX generation to Support R&D.
  • Transfer the results of the advanced research on AI/CG solutions to solve real-world problems, and land them in various Huawei products.
  • Provide expert opinions on relevant fields by summarizing research findings in high-quality papers or patents.

The total target annual compensation (based on 2,080 hours per year) ranges from $58,000 to $104,000 depending on education, experience, and demonstrated expertise.

About the ideal candidate

  • Bachelors of Science or higher in computer science or related fields with a focus on computer graphics, computer vision or machine learning.
  • Backgrounds in machine learning and deep learning, e.g., Symbolic regression, DNN, GAN, ViT, and Diffusion techniques
  • Experienced on dense estimation including but not limited to procedural generation SVBRDF, super-resolution, inpainting, neural rendering, etc.
  • Experienced in Python, PyTorch, TensorFlow, etc. and a track record of translating ideas into research prototypes quickly

Skills

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