Job Responsibilities:
1. Large model engineering implementation: Responsible for key aspects such as inference optimization and deployment.
2. Large model application research and implementation: involving AI-Agent, RAG, LangChain and other technologies.
3. Model architecture design and optimization: improve model performance according to business needs.
4. NLP technology platform and tool construction: improve the team’s R&D efficiency.
5. Systematic application of research results: Apply the latest research results to large model systems.
 

Job Requirements:
1. Proficient in Python, familiar with Linux environment development, and proficient in applying the deep learning framework TensorFlow or PyTorch.
2. 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.
3. Have the ability to analyze, define and solve problems, and have continuous self-driving force to face challenges.
4. Applicants with practical experience in fine-tuning large language models or strong research capabilities will be given priority.