携程服务端Agent开发工程师(MJ034298)
社招全职3年以上国际业务开发地点:上海状态:招聘
工作描述
任职要求 1、计算机相关专业全日制本科以上学历,3年以上开发工作经验; 2、有较强的学习能力、问题分析和解决能力,以及良好的团队合作精神; 3、了解业界常见的Agent技术和框架,有 Agent/Workflow 的开发经验; 4、熟悉大模型基础原理,熟练掌握Prompt Engineering,有RAG、模型微调(SFT/RLHF)或相关应用落地经验; 5、具备数据驱动思维,能够设计Agent效果评估…
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包括英文材料
学历+
AI agent+
https://www.ibm.com/think/ai-agents
Your one-stop resource for gaining in-depth knowledge and hands-on applications of AI agents.
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
Prompt+
https://cloud.google.com/vertex-ai/generative-ai/docs/learn/prompts/introduction-prompt-design
A prompt is a natural language request submitted to a language model to receive a response back.
https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering
These techniques aren't recommended for reasoning models like gpt-5 and o-series models.
https://www.youtube.com/watch?v=LWiMwhDZ9as
Learn and master the fundamentals of Prompt Engineering and LLMs with this 5-HOUR Prompt Engineering Crash Course!
RAG+
https://www.youtube.com/watch?v=sVcwVQRHIc8
Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer.
SFT+
https://cameronrwolfe.substack.com/p/understanding-and-using-supervised
Understanding how SFT works from the idea to a working implementation...
RLHF+
[英文] What is RLHF?
https://aws.amazon.com/what-is/reinforcement-learning-from-human-feedback/
Reinforcement learning from human feedback (RLHF) is a machine learning (ML) technique that uses human feedback to optimize ML models to self-learn more efficiently.
https://www.ibm.com/think/topics/rlhf
Reinforcement learning from human feedback (RLHF) is a machine learning technique in which a “reward model” is trained with direct human feedback, then used to optimize the performance of an artificial intelligence agent through reinforcement learning.
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