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Huawei Canada

Principal AI Research Engineer

Reposted 22 Days Ago
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In-Office
Vancouver, BC, CAN
Senior level
In-Office
Vancouver, BC, CAN
Senior level
Lead advanced AI research projects focused on computer graphics and rendering techniques, mentoring junior engineers and translating ideas into research prototypes.
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Huawei Canada has an immediate permanent opening for a full-time permanent Principal AI Research 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:

  • Develop and lead projects, team ideas, and mentor junior engineers.

  • Conduct advanced research and engineering on AI-based rendering techniques including but not limited to Neural Rendering acceleration, Neural material representation, Neural Texture Compression, etc.

  • Transfer advanced research AI/CG solutions to solving real-world problems that will be integrated in various Huawei products.

  • Provide expert opinions on relevant fields by summarizing research findings in high-quality papers or patents.

The base salary for this position ranges from $121,000 to $230,000 depending on education, experience and demonstrated expertise.

What you’ll bring to the team:

  • Solid industry engineering level and experience over 5 years.

  • Industry work experience in CG related field over 3 years with hands-on development.

  • MSc / Ph.D. in computer science or related fields with a focus on applied ML to computer graphics or computer vision.

  • Extensive Background in machine learning and deep learning, e.g., DNN, GAN, ViT, and Diffusion techniques.

  • Experienced in neural representation/rendering such as NerF, Gaussian Splatting, neural rendering, procedural generation, SVBRDF, etc.

  • Experienced in Python, PyTorch, TensorFlow, etc. and a track record of translating ideas into research prototypes quickly.

  • Published Papers at relevant conferences or Journals such as SIGGRAPH, Eurographics, TOG, CVPR, ICCV, ECCV, TPAMI.

  • Experienced programming skills on shading languages, e.g., glsl, hlsl, etc.

  • Experienced in building large-scale machine learning solutions for general computer vision/graphics topics including model design, data collection/augmentation evaluation, etc.

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