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Open nowPosted 83 days ago

豆包大模型Agent Harness算法工程师 - Data AML

ByteDance19,258 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now豆包大模型Agent Harness算法工程师 - Data AMLByteDance · Shanghai, Chinese Mainland
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The clock on this job

Early applications get read.

11.3% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 23 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.3%7 days
  4. 17.6%14 days
  5. 34.3%30 days
  6. 43.5%60 days
This job: posted 83 days ago

ByteDance median: 23 days open

The posting

团队介绍:Data AML是字节跳动的机器学习中台,为抖音/今日头条/西瓜视频等业务提供推荐/广告/CV/语音/NLP的训练和推理系统。为公司内业务部门提供强大的机器学习算力,并在这些业务的问题上研究一些具有通用性和创新性的算法。同时,也通过火山引擎将一些机器学习/推荐系统的核心能力提供给外部企业客户。

1、参与火山方舟Managed-Agent相关的算法研发工作,参与方舟自有Harness的技术架构选型、设计、优化; 2、优化方舟自有Harness,包括但不限于Harness的运行模式、Buildin-Tools、Context机制、Multi-Agent协作调度、智能的辅助能力(模型选择、Advisor、Grader、Rlaphloop等等); 3、和评测团队一起构建面向Harness迭代的Agent评测,构建全面、有效的Agent Harness端到端评测; 4、定义和实现Harness领域的前沿创新,与模型团队深度合作,参与实现模型与Harness的共同进化,从Harness的角度实现Harness与模型的深度适配。

1、2027届获得本科及以上学历,专业不限; 2、对Agent Harness有技术热情,对大模型和Agent有较深入的理解,有Agent Harness的优化经验;有使用AI Agent工具进行软件开发的经验;在软件开发领域具有较强的学习能力;能够在AI辅助下,进行有质量保证的编程工作; 3、了解模型和Agent Harness的基本机制及其技术原理(如LLM API、Reasoning、KV Cache、ToolUse、Skills、ReAct、Multi-Agent、MCP、A2A、FunctionCalling); 4、了解和Agent评估方法、Agent构建、RAG检索技术等; 5、了解流行的各类Agent应用的原理和实现细节,如:OpenClaw、HermesAgent、Codex、ClaudeCode、Managed-Agents。

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