Researcher - GPU & AI Rendering

Huawei Canada has an immediate 12-month contract opening for a Researcher.

About the team:

The Software-Hardware System Optimization Lab continuously improves the power efficiency and performance of smartphone products through software-hardware systems optimization and architecture innovation. We keep tracking the trends of cutting-edge technologies, building the competitive strength of mobile AI, graphics, multimedia, and software architecture for mobile phone products.

About the job:

• Conduct research on GPU-accelerated rendering techniques, including real-time ray tracing, rasterization, and hybrid methods.

• Investigate AI-driven rendering approaches such as neural radiance fields (NeRF), GAN-based synthesis, denoising, and super-resolution.

• Prototype and evaluate new algorithms that leverage GPU architectures for enhanced visual fidelity and performance.

• Explore the integration of AI models into rendering workflows, including differentiable rendering and learned shading.

• Publish findings in top-tier conferences and journals (e.g., SIGGRAPH, CVPR, NeurIPS).

• Collaborate with cross-functional teams to validate research in real-world applications and contribute to long-term innovation roadmaps.

About the ideal candidate:

• Master’s degree required, Ph.D. is an asset. Preferred in Computer Graphics, Computer Science, Electrical Engineering, or a related field.

• Strong understanding of GPU architectures and graphics APIs (e.g., Vulkan, Metal, DirectX, CUDA).

• Experience with AI frameworks (e.g., PyTorch, TensorFlow) and their application in visual computing.

• Solid foundation in rendering algorithms, image synthesis, and performance optimization.

• Demonstrated ability to conduct independent research and communicate results effectively.

• Prior publications or research contributions in graphics, AI rendering, or visual computing.

• Experience with rendering engines (e.g., Unity, Unreal, Blender) or custom GPU pipelines.

• Familiarity with neural graphics primitives and differentiable rendering frameworks.