AI应用工程师（J10575）

到岗时间：不限 婚况要求：不限 工作职责: 1. 应用设计开发 Application Design and Development 1.1 负责公司 AI 产品的架构设计与核心代码开发（如智能助手、知识库、自动化流程等），主导大模型（LLM）在业务场景中的落地应用。 1.1 Responsible for the architectural design and core code development of the company's AI products (e.g., intelligent assistants, knowledge bases, automation workflows), and leading the implementation of large language models (LLMs) in business scenarios. 1.2 负责预训练模型的微调（Fine-tuning）、提示词工程（Prompt Engineering）、RAG（检索增强生成）架构搭建，以及模型在推理端的性能优化与部署。 1.2 Responsible for fine-tuning pre-trained models, prompt engineering, building RAG (Retrieval-Augmented Generation) architecture, as well as optimizing and deploying models for inference performance. 1.3 负责构建高效的数据处理流水线，负责业务数据的清洗、标注、向量化存储及管理，为模型训练和推理提供高质量数据支持。 1.3 Responsible for building efficient data processing pipelines, including data cleaning, labeling, vectorized storage and management, to provide high-quality data support for model training and inference. 1.4 负责跟踪业界最新的 AI 应用技术（如 Agent、Multi-modal 等），解决应用过程中的幻觉、延迟、安全性等技术难题。 1.4 Responsible for tracking the latest AI application technologies (e.g., Agent, Multi-modal, etc.) and solving technical challenges such as hallucinations, latency, and security in the application process. 2.1 负责 AI 相关培训资料编写。 2.1 Responsible for preparing AI-related training materials. 2.2 负责员工 AI 应用培训。 2.2 Responsible for conducting AI application training for employees. 3.1 制定点检计划，负责点检 AI 服务器及应用运行情况，确保服务正常。 3.1 Responsible for developing inspection plans and checking the operation status of AI servers and applications to ensure normal service. 3.2 按公司要求定期总结工作汇报。 3.2 Responsible for regularly summarizing work and providing reports as required by the company. 任职资格: 1.研究生及以上学历，计算机科学与技术、人工智能、软件工程专业。 Master's degree or above in Computer Science and Technology, Artificial Intelligence, or Software Engineering. 2.具有 2 年及以上 AI 相关领域全职工作经验，有完整的 AI 项目从 0 到 1 落地经验者优先。 At least 2 years of full-time work experience in AI-related fields; experience in delivering complete AI projects from 0 to 1 is preferred. 3.精通 Python 编程，熟悉常用的 AI 开发框架（如 PyTorch, TensorFlow, LangChain, LlamaIndex 等），具备良好的代码规范和系统设计能力。 Proficient in Python programming, familiar with common AI development frameworks (e.g., PyTorch, TensorFlow, LangChain, LlamaIndex, etc.), and possess good coding standards and system design skills. 4.熟悉主流大模型（如 Llama, Qwen, ChatGLM 等）的原理及应用开发。 Familiar with the principles and application development of mainstream large language models (e.g., Llama, Qwen, ChatGLM, etc.). 5.熟悉向量数据库（如 Milvus, Pinecone, Elasticsearch 等）的使用与优化。 Familiar with the use and optimization of vector databases (e.g., Milvus, Pinecone, Elasticsearch, etc.). 6.熟悉 Linux 开发环境，掌握 Docker、Kubernetes 等容器化部署技术。 Familiar with the Linux development environment, and proficient in containerized deployment technologies such as Docker and Kubernetes. 7.具备良好的业务理解能力，能够将模糊的业务需求转化为具体的技术解决方案。 Strong business understanding skills, with the ability to translate ambiguous business requirements into concrete technical solutions.