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Open nowPosted 191 days ago

大模型Agent研究工程师-Seed

ByteDance19,268 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now大模型Agent研究工程师-SeedByteDance · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

11.9% 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. 2.1%1 day
  2. 4.4%3 days
  3. 11.9%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 191 days ago

ByteDance median: 9 days open

The posting

1、负责大模型Agent系统的研究与工程落地，围绕复杂任务执行持续优化Agent效果，包括但不限于harness、memory、context compression、planning/execution、multi-agent collaboration等关键机制； 2、设计并实现面向大规模Agent任务的Benchmark、评测集、指标体系与自动化评测流程，支持模型训练、版本迭代和产品上线； 3、建设和优化Agent的关键能力接口与运行机制，包括Prompt、Tool use、任务拆解、上下文管理、模型编排、执行策略等； 4、参与训练数据构造、样本优化与效果分析，提升模型在Agent场景下的性能、稳定性与易用性； 5、与算法、平台、产品等团队协作，推动Agent在编程、研究、运营、知识工作等场景中的落地，并围绕效果、成本、稳定性持续优化。

1、对语言大模型、多模态大模型、智能代理Agent技术以及大模型部署流程有较好的理解； 2、具备扎实的软件工程能力与机器学习基础，能够独立完成复杂系统设计、开发与优化； 3、具备基于大语言模型构建复杂Agent系统的实践经验，理解任务规划、执行、记忆、协作等关键机制； 4、具备Prompt设计、模型应用开发、模型编排或相关产品化经验； 5、具备良好的沟通与协作能力，能够与研究、产品、工程团队高效配合推进复杂问题落地； 6、熟悉常见Agent Benchmark或相关评测方法，有Benchmark工程化、自动评测、效果分析经验，或有语言模型强化学习（RL）、多智能体系统经验者优先；持续关注Agent、多智能体、自动评测、训练优化等前沿研究与行业进展。

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