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Job Description
Model Training & Optimization: Design and execute training pipelines for large-scale AIGC models, including data curation, training stability, and performance optimization. Apply large-scale diffusion models to practical visual tasks such as low-light enhancement.
Architecture & System Design: Contribute to the architecture and algorithm design for AIGC and large multi-modality models spanning image and video, from foundational model training through to post-training alignment and quality enhancement.
Post-training & Alignment: Implement and advance post-training methods for diffusion-based multimodal large models to improve output quality.
Capability Exploration: Investigate and prototype emerging capabilities such as multi-modal understanding and visual content generation.
Frontier Research: Track cutting-edge AIGC research, drive project planning, and deliver production-grade implementations. Contribute to the academic community through publications at top-tier venues.
Requirements
Master's degree or above in Computer Science or related fields
First-author publication(s) at top-tier venues (CVPR/ICLR/ECCV/ICML/NeurIPS/TPAMI) on diffusion-based multimodal generation, particularly post-training/alignment methods that improve generation quality;
Have experience in multimodal large model across image generation or video generation
Proficient in PyTorch;
Good programming skills in Python, C++, and CUDA;
Strong problem-solving skills, innovative thinking, and excellent team collaboration/communication skills.
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SG
