About the Team
Welcome to the GAI-Vision team, where we lead the way in developing foundational models for multi-modal visual understanding and generation. Our mission is to solve the challenge of visual intelligence in AI. We conduct cutting-edge research on areas such as vision and language, large-scale vision models, and generative foundation models. Comprising experienced research scientists and engineers, our team is dedicated to pushing the boundaries of foundation model research and implementing our innovations across diverse application scenarios. We foster a feedback-driven environment to continuously enhance our foundation technologies. Come join us in shaping the future of AI and transforming the product experience for users worldwide.
Responsibilities
- Explore large-scale/ultra-large-scale visual models and perform system optimization. This includes data construction, instruction fine-tuning, preference alignment, and model optimization.
- Conduct cutting-edge research and development in computer vision, natural language processing, machine learning and general artificial intelligence, especially in the areas of multi-modality, vision and language.
- Publish our latest research results and help to build our brand in the research community.
- Explore vision/multi-modality application models, and contribute to the development of new technologies and products leveraging artificial intelligence.
Qualifications
- Possess research and practical experience in one or more areas of computer vision, encompassing:
- Multi-modal understanding
- Vision-language models (e.g., video captioning, VQA, Text-to-video retrieval, and other related topics)
- Large-scale training
- RLHF
- Multimodal generation (e.g., text-to-image, image, video, 3D generation and editing)
- Diffusion models, GANs, transformers for generation tasks.
- Work with large-scale datasets, and build large-scale datasets to scale up foundation models.
- Experience with vision-language models and apply them in various downstream tasks.
- Demonstrate impactful publications in leading AI conferences (e.g., CVPR, ECCV, ICCV, NeurIPS, ICLR, SIGGRAPH, SIGGRAPH Asia) and journals (e.g., TPAMI, JMLR).
- Proficiency in one of the differentiable programming frameworks such as PyTorch, TensorFlow, JAX, etc.
- Possess coding skills in C/C++ and Python.
- Proven track record of high-impact research.
- Collaborate effectively with team members.
- Ability to work independently.
Preferred Qualifications
- Recognition with best paper awards or equivalent accolades in renowned conferences.
- Achievement as a winner in international academic competitions.