Agent算法实习生（J104743）
Core
Intern role focused on optimizing search algorithms (recall, ranking, relevance) and applying Large Language Models (LLMs) to search scenarios like query understanding and intent recognition.
Role type
Search Algorithm Intern (LLM & Agent focus)
Builds
Search engine components including ranking models, query understanding systems, and data labeling pipelines.
Domain
Search, Recommendation, NLP
Deliverable
production ML models
Required skills
Python, NumPy, Pandas, Scikit-learn, PyTorch or TensorFlow, LLM fundamentals, Embedding, Rerank, Prompt Engineering, SFT/LoRA, A/B testing
Preferred skills
Coding Agent usage (Claude Code, Cursor), Search/Rec/NLP project experience, Data construction (weak labeling/synthetic data), DPO
Technologies
Python, PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn, LLMs, Embedding models, Rerank models, Coding Agents
Responsibilities
Optimize search algorithms for recall, ranking, and relevance; Model LLMs for query understanding and intent recognition; Construct and clean search samples (Query-Doc, clicks); Train and evaluate models using feature engineering and fine-tuning; Utilize Coding Agents to automate analysis and diagnostics; Design and execute A/B experiments to measure impact.