Senior Algorithm Engineer - Multimodal Generation

About the Company

We are collaborating with a distinguished global leader in information and communications technology (ICT) infrastructure and smart devices, delivering comprehensive AI solutions across full-stack, all-scenario applications for product and service carriers, businesses, governments, and individual users worldwide.

Job Responsibilities

• Engage in research and development of large multimodal models (LMMs) and AI-generated content (AIGC) algorithms, emphasizing image and video generation and editing while progressively enhancing fundamental algorithmic capabilities such as multimodal controllable generation, video continuation, image and video editing, and integrated generation-and-understanding models.
• Investigate and assess the latest advancements in video generation and unified generation-understanding models by monitoring breakthroughs in both academic and industry settings focused on image, video, and multimodal large models, initiating new functional capabilities and applications spanning device, cloud, and autonomous driving domains.
• Collaborate tightly with product, system, and engineering teams to convert innovative algorithmic research into practical, reliable product implementations, ensuring stable deployment of technologies in real-world business environments.

Job Requirements

• Possess a Master's degree or higher in Computer Science, Artificial Intelligence, or a related engineering discipline; a PhD is preferred.
• Have between one and five years of pertinent research or development experience, with strong knowledge in one or more of these fields: image/video generation and editing, multimodal large models, unified generation-and-understanding models, reinforcement learning; recognized top-tier authorship such as first-author publications at conferences like CVPR, ICCV, ECCV, NeurIPS, ACMMM, ACL, or ICLR is an advantage.
• Demonstrate advanced skills in algorithm design and deep learning model development, proficient programming abilities in Python and C++, and practical experience using widely adopted AI frameworks including PyTorch or TensorFlow, with capabilities to independently architect, train, and analyze models experimentally.
• Exposure to image or video generation and editing algorithms is favorable; experience handling large-scale visual data annotation, cleansing, and analysis is preferred.
• Maintain a broad technological perspective with the capacity to stay abreast of cutting-edge progress in multimodal and generative AI from academic and industrial research.
• Exhibit strong autonomous problem-solving skills and thrive in team-based collaborative environments.

Additional Information

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