Overview
Seeking technically driven research leaders to spearhead the design, development, optimization, and exploration of multimodal large models. This role focuses on building next-generation intelligent service-aware systems and edge-cloud integrated AI architectures across devices, automotive, and cloud platforms, aiming to develop industry-leading multimodal large language models.
Responsibilities:
- Conduct technical research on multimodal foundation models, including but not limited to pre-training, post-training, theoretical modeling, and capability evaluation, targeting applications in Huawei's consumer devices, automotive systems, and cloud platforms.
- Design and optimize the architecture of multimodal foundation models.
- Develop and optimize engineering solutions and algorithms for efficient training and inference of multimodal models.
- Continuously track the latest research developments in the field of multimodal foundation models; lead exploration and validation of cutting-edge technologies.
Requirements:
- Strong self-motivation, intellectual curiosity, and a passion for exploring new knowledge and emerging domains. Solid logical thinking and analytical skills.
- Proficient in deep learning; candidates with hands-on experience in training and inference of large models (7B+ LLMs/VLMs/VLAs) are highly preferred.
- Publications in top-tier conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, T-RO) are strongly valued.
- Familiarity with techniques such as prompt engineering and post-training; prior experience is a plus.
- Proficient in programming languages such as C++ and Python, with strong coding and software development skills.
