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Open nowPosted 228 days ago

Agent策略优化工程师 - 火山引擎

ByteDance19,268 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen nowAgent策略优化工程师 - 火山引擎ByteDance · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 9 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 228 days ago

ByteDance median: 9 days open

The posting

团队介绍：火山引擎是字节跳动旗下云和AI服务平台，将字节跳动快速发展过程中积累的增长方法、技术能力和应用工具开放给外部企业，通过云和AI技术，推进企业智能化转型，激发增长潜能。

1、Agent Loop设计与优化：负责Agent核心链路（Planning/Reasoning/Tool Use/Reflection）的策略设计与持续优化，提升复杂任务的成功率、稳定性与执行效率，攻坚长程任务（Long-horizon Execution）下的上下文管理与错误恢复； 2、Context Engineering&Memory系统：设计Agent的上下文工程方案与记忆系统（短期/长期/情景/语义记忆），落地记忆的写入、检索、压缩、更新与遗忘策略，支撑用户级个性化与跨会话一致性； 3、Data Engine：基于线上Trace、用户反馈与评估信号构建数据闭环，负责轨迹数据构造、数据生成与高质量SFT/RL数据的产出； 4、Learning Loop闭环：推动SFT/DPO/Agentic RL（GRPO/DAPO等）等Post-training策略在业务场景的落地，让Agent在线上数据驱动下持续进化； 5、评估体系建设：构建覆盖离线Benchmark、在线A/B、案例回归的多层次评估体系，沉淀负面案例库，支撑算法策略快速迭代。

1、计算机、人工智能、数学等相关专业本科及以上学历，3年以上算法/AI工程相关经验； 2、熟悉大模型技术栈：Transformer、Prompt Engineering、RAG、Function Calling/MCP、Context Engineering，了解主流模型（GPT、Claude、Gemini、Qwen、DeepSeek等）的能力边界与适用场景； 3、扎实的Python工程能力，熟悉至少一种主流Agent框架（LangGraph、LlamaIndex、AutoGen、Dify、CrewAI等）或具备自研Agent框架的经验； 4、有复杂Agent系统的策略优化经验，熟悉ReAct、Reflexion、Plan-and-Execute、Tree of Thoughts等范式，有显著提升任务成功率/稳定性/成本的实战案例； 5、有大模型Post-training经验（SFT/DPO/PPO/GRPO/DAPO），了解Agentic RL相关方法； 6、熟悉Agent评估框架（SWE-bench、GAIA、AgentBench等）。

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