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Algorithm Research Lead
2 weeks ago
Research and optimize content generation models (text, image, audio, 3D models, etc.) to address challenges such as generation quality, diversity, controllability, and efficiency.
- Aim to improve user experience and production effectiveness, and support the productization of algorithms.
- Conduct algorithm training and optimization in areas such as image generation, multi-modal large models, and few-shot learning.
- Address the industrial deployment of multimodal generative models and actively explore model design and optimization in an R&D context
**Job Requirements**
- PhD (preferably fulltime) in Computer Science, Artificial Intelligence, Mathematics, or related fields.
- Proficient in machine learning and deep learning fundamentals, and familiar with mainstream AIGC frameworks, including GAN, VAE, VQGAN, Diffusion models, etc.
- Familiar with generation model extensions such as ControlNet, LoRA, and Text Inversion.
- Familiar with multi-modal models like CLIP, ERNIE-ViL, and other transformer-based cross-modal representation models. Hands-on experience in NLP, multi-modal learning, or AI-generated content is a strong plus.
- Strong learning ability, clear logical thinking, excellent communication skills, and a high level of curiosity.
- Good teamwork and interpersonal communication skills.
- Fluency in both English and Mandarin to deal with international stakeholders and stakeholders who are based in HQ
