Computer Vision (Camera) Researcher

This role involves working closely with multiple discipline colleagues within the team and camera technology innovation laboratory, including imaging algorithms, AI, camera sensor HW, and colour and spectral experts.

Job Descriptions:

• Research and develop AI models for computational photography, image/video enhancement, colour processing, ISP pipeline algorithms, spanning architectures such as vision-language models, diffusion image/video transformer models, etc.
• Adopt emerging AI breakthroughs into high-impact innovations for mobile imaging
• Implement research ideas in Pytorch or Tensorflow and continue with NPU compatible model optimization to enable a rapid integration into Huawei devices
• Architect roadmaps and lead the execution of complex integration projects to enhance the on-device vision pipeline
• Identify data requirements, guide collection and annotation efforts, and build high-quality synthetic data creation pipeline that enables reliable model training
• Identify model failure cases and develop targeted solutions to improve performance in critical real-world scenarios
• Partner with other algorithm and hardware imaging teams to define key problems and deliver effective embedded AI solutions for joint HW+SW architectures

Qualifications and detailed requirements:

• PhD or MSc in the field of computer vision, machine learning, signal/image processing, or associated discipline, with years-long track record of developing AI solutions for mobile imaging platforms and products
• Deep understanding of the theory behind the machine learning, deep learning methods and imaging technologies.
• Proven ability to build, train, fine-tune and assess deep learning models for vision tasks such generative AI, image/video restoration, 3D-vision and multimodal learning etc.
• Proficient in state-of-the-art architectures including Vision Transformers (ViT), Diffusion Transformers (DiT), and Latent Diffusion Models (LDM) for advanced image and video manipulation. Experienced in the adaptation and distillation of billion-parameter models, successfully deploying them to solve complex real-world challenges such as multi-frame super-resolution, video deblurring, interpolation, stabilization and reference-based restoration.
• Strong competency in Python and deep learning libraries like Pytorch and Tensorflow and experience in ONNX and NPU-compatible model optimization is a plus
• Familiar with mobile camera imaging and image/video processing algorithms and AI solutions
• Ability to navigate and innovate in rapidly evolving technical landscapes with ambitious and often ambiguous goals.
• Big advantage for contestants from international competitions in computer science, mathematics, or physics (e.g. IOI, IMO, ICPC, IPhO, IChO)