NLP Algorithm Engineer Intern

Key Responsibilities

• LLM Application Development: Participate in the development of LLM-based applications, including Q&A systems, Agents, and algorithmic workflow systems.
• Workflow & Prompt Engineering: Assist in workflow development, as well as Prompt design and optimization to improve model performance.
• Agent Capabilities: Assist in implementing Tool Use (Function Calling) and foundational multi-turn dialogue logic.
• Core NLP Tasks: Implement tasks such as text classification, information extraction, and semantic matching.
• Model Modeling: Participate in small-scale modeling (classification/labeling tasks) and performance optimization.
• Data Management: Perform data cleaning, basic feature engineering, and result analysis.

Job Requirements

Basic Requirements

• Coding Proficiency: Proficient in Python with good coding habits and strong problem-solving skills.
• NLP Fundamentals: Familiar with common NLP tasks (Text Classification, NER, Semantic Matching, etc.) and their standard methodologies.
• Modeling Experience: Capable of independently completing the training and fine-tuning of simple classification or labeling models.
• Theoretical Knowledge: Deep understanding of machine learning and NLP fundamentals.