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As a Mobile Camera Imaging AI Research Engineer, you will dig deep into research, development, implementing and optimization of AI based solutions for full pipeline transferring camera sensor captured photons into beautiful images and video. You will master the application of deep learning models, including vision-language, generative, and color mapping approaches, to address complex challenges in Huawei smartphone camera systems. In this role, you will leverage large-scale models to develop state-of-the-art AI algorithms for a diverse range of image and video restoration tasks, including but not limited to super-resolution, deblurring, video interpolation, video understanding and motion manipulation. Beyond research, you will be responsible for making these solutions production-worthy by implementing rigorous performance optimizations to ensure low-latency, high-efficiency deployment in real-world environments. 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 color and spectral experts. This will include learning from and working with world class leading competence on mobile imaging sensors, spectral sensing and emerging novel photon capturing solutions. You will also share your gathered competence, practical experience and knowledge on embedding AI based solutions into mobile camera image processing platforms. You will develop related image and video processing algorithms, help define problems, agree on clear performance metrics, and deliver solutions that perform reliably on real-world data. Job Descriptions: Research and develop AI models for computational photography, image/video enhancement, color 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