Reproduce algorithms from the latest top-tier conference papers, debug models, and conduct extensive training and testing.
Analyze limitations of existing models, propose improvement strategies, and design novel algorithms to enhance generation quality.
Collect, clean, annotate, or generate large-scale 3D datasets for model training.
Discuss technical solutions with team members, document experimental findings, and participate in code reviews.
Requirements:
Minimum Qualifications: Ph.D. in Computer Science or a related field, with a background in computer graphics, computer vision, or machine learning, and a focus on 3D generative AI.
Experience in training large-scale 3D models and data processing.
Proficient in Python, familiar with theoretical principles and implementation of Diffusion algorithms, 3D model representation, 3D content generation, and related technologies. Stay updated on the latest advancements in the field.
Passionate about technology, clear-thinking, strong problem-solving and analytical skills, excellent communication abilities, and a collaborative mindset.
