Job Description:
- 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.
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