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Open nowPosted 48 days ago

大模型算法工程师

dcar/referral674 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now大模型算法工程师dcar/referral · Beijing, Chinese Mainland

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Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 48 days ago

The posting

1、智能体（Agent）系统核心建设： - 负责基于大语言模型（LLM）的智能体系统设计、开发与迭代； - 重点打造应用于 C 端 Chatbot（如智能导购、个人助理、AI 搜索）的 Agent 架构，引入安全护栏（Guardrails）机制以确保输出的确定性，全面提升全链路的用户体验与任务完成率； 2、Agent 编排与控制工程（Orchestration & Harness）： - 探索通用、高质量的提示词范式，设计并构建管理工具调用、技能抽象与多智能体协同（Multi-Agent）的动态调度引擎； - 赋予系统多步骤编排、自主规划、记忆机制、执行结果反馈与安全纠错能力，大幅提升模型在复杂意图澄清、跨领域对比分析、多轮对话一致性等高难度任务中的表现； 3、LLM 模型领域后训练： - 建设模型评测集、做对比选型与领域后训练全流程建设（含 SFT、RLHF/RLAIF）； - 打通 C 端线上交互数据的自动化回流链路，构建数据飞轮； - 跟进学术与工业界前沿进展，持续提升模型在业务特定领域任务上的表现； 联合 AI-infra 团队优化响应速度与训推资源； 4、知识图谱与RAG建设： - 针对海量、异构业务数据（如视频、图文、车型库、商品 SKU），设计适合 Agent 引用与对齐的知识图谱与向量索引结构，引入自进化机制，并依托前沿的检索技术和上下文窗口压缩技术，与 LLM 深度融合，实现高精准、低延迟的问答与智能搜索体验； 5、跨团队协同与工程落地： - 和产品、研发团队配合，随版本规划开发上线，并快速响应线上的效果调优与稳定性追查需求。

1、计算机、数学或数据科学等相关专业硕士及以上学历，具备 3 年以上大语言模型（LLM）相关研发经验，深刻理解 Transformer 架构，熟悉 SFT、RLHF/RLAIF 等后训练全流程并有实际微调落地经验； 2、熟悉主流 Agent 框架（如 LangChain, LangGraph, AutoGen, Eino）或其底层原理，具备高并发、低延迟分布式调度系统的设计经验，能独立完成多智能体协同（Multi-Agent）、复杂任务流编排、记忆机制及状态机管理； 3、熟练掌握高级 RAG 技术（如查询改写、混合检索、重排）及数据库应用，拥有文本和多模态搜索经验，熟悉知识图谱的构建与融合； 4、精通 Python/Go 且具备全栈工程意识，熟练运用前沿 AI 工具进行超级个体式的高效研发（Vibe Coding）；技术视野开阔，有责无界，能快速验证从算法思路、前后端研发到产品原型的全链路闭环； 5、加分项：有知名 C 端 Chatbot、智能导购、AI 搜索等大规模线上业务落地经验者优先；在业界实操过领域大模型（Domain LLM）后训练或对齐，有开源社区影响力或学术成果者优先。

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