Large Model Algorithm Researcher

Roles & Responsibilities

1. Explore and research new technologies and algorithms related to large model pre-training and alignment, including but not limited to: pre-training, training frameworks, supervised fine-tuning (SFT), reinforcement learning, etc., as well as applications in general dialogue, mathematics, code generation, reasoning, and other scenarios.
2. Stay current with cutting-edge advances in the large model domain, and apply them to R&D and production to continuously improve the general and specialized capabilities of large models.
3. Mentor research interns in related areas.

1. Proficient in Python, comfortable with Linux development environments, and experienced with deep learning frameworks such as TensorFlow or PyTorch.
2. Continuously engaged with state-of-the-art deep learning techniques, familiar with cutting-edge deep learning algorithms and model architectures including Transformer.
3. Strong analytical and problem-solving skills, with the self-motivation and drive to tackle challenging problems.
4. Experience in large language model pre-training, alignment techniques, or reinforcement learning is preferred. A strong research track record —such as high-quality publications at top-tier conferences in machine learning, artificial intelligence, NLP, or CV — is also highly valued.