Job Responsibilities
- Large model engineering implementation: Responsible for key aspects such as inference optimization and deployment.
- Large model application research and implementation: involving AI-Agent, RAG, LangChain and other technologies.
- Model architecture design and optimization: improve model performance according to business needs.
- NLP technology platform and tool construction: improve the team’s R&D efficiency.
- Systematic application of research results: Apply the latest research results to large model systems.
Job Requirements
- Proficient in Python, familiar with Linux environment development, and proficient in applying the deep learning framework TensorFlow or PyTorch.
- Continue to follow up on cutting-edge deep learning technology, understand cutting-edge deep learning related algorithms, and be familiar with model structures such as Transformer.
- Have the ability to analyze, define and solve problems, and have continuous self-driving force to face challenges.
- Applicants with practical experience in fine-tuning large language models or strong research capabilities will be given priority.