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Open nowPosted 195 days ago

AI 应用开发工程师（智能投放方向）

lx3qcyzne8/index52 open roles

Where
Guangzhou, Guangdong, Chinese Mainland
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Your applicationOpen nowAI 应用开发工程师（智能投放方向）lx3qcyzne8/index · Guangzhou, Guangdong, 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 195 days ago

The posting

一、岗位介绍 团队专注广告投放技术，长期深耕素材生产与投放全流程的智能化。当前正在从0到1打造一套AI驱动的智能广告投放与治理系统：从素材理解、内容生成，到投放策略与效果优化，逐步实现自动化与智能决策。所以我们想招聘一位能把AI技术真正落到业务里的伙伴，而不仅仅是会用模型的人。

二、岗位职责 1. AI智能投放系统开发与落地：负责 AI 驱动的广告投放系统后端开发与落地，围绕素材理解、内容生成与投放策略等核心环节，完成大模型应用开发、AI Agent 编排及 RAG 能力建设，并持续推动这些能力在真实业务中的应用与优化，逐步形成投放决策闭环。 2. RAG系统设计与实现：负责 RAG 检索增强系统的设计与实现，覆盖文档解析、向量化、多路召回与重排序等关键环节，支持素材、策略与案例的高效检索与复用，提升模型在实际业务中的准确性与可用性。 3. 大模型应用工程化与输出治理：负责大模型能力的工程化落地与输出治理，包括能力封装、调用规范设计及结果稳定性控制，并通过 prompt 防护、结构化约束与内容校验等机制，保障 AI 输出的准确性、安全性与可控性。 4. AI评估与迭代体系建设：搭建 AI 能力评估与持续优化机制，基于 RAGAS、LLM-as-a-judge等方法建立评估标准，通过回归测试、A/B 测试与线上监控不断优化效果，形成数据驱动的迭代体系。 5. 工程化与性能优化：负责 AI 服务的工程化建设与性能优化，包括系统稳定性、响应速度与模型调用成本优化，并完善监控与告警机制，协同产品与算法团队推进 MVP 与持续迭代。

三、任职要求 1. 后端开发经验：本科及以上学历，3年及以上后端开发经验，具备完整系统开发经验，能独立完成系统设计与上线。 2. 技术栈：熟练使用 Python（主力语言），有 Go/Java 经验更佳。 3. AI应用能力：具备 LLM 应用开发经验，参与过 RAG 或 Agent 项目落地，理解 RAG 基本架构（召回、重排、混合检索等）。 4. 业务理解与数据思维：具备数据驱动意识，能够将 AI技术转化为实际业务价值。 5. 团队氛围好，办公地点交通便利，免费提供三餐

四、加分项 1. 业务与行业经验：有广告投放、素材管理或智能创意相关经验，熟悉广告技术或 MarTech 体系，了解短剧/素材生产与投放流程者优先。 2. AI产品与工程经验：有 AI Agent 或 LLM 产品从 0 到 1 的落地经验，熟悉 LangChain、LlamaIndex 等主流框架，具备 prompt 工程或 guardrails 实践经验。 3. 模型能力与技术背景：具备模型评估经验（如 RAGAS、LLM-as-a-judge 等），有计算机/AI相关专业背景，或具备多模态/CV开发经验者优先。

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