阿里巴巴日常实习生-1688-大模型应用算法
实习兼职阿里巴巴日常实习生地点:杭州状态:招聘
任职要求
* 计算机、人工智能、数学等相关专业在读(本科大三及以上 / 硕士 / 博士),可实习 3 个月以上。 * 熟悉 Transformer、LLM 基础原理,了解 SFT / RLHF / RAG / Agent 等主流技术范式之一。 * 具备扎实的 Python 编码能力,熟悉…
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工作职责
(1)参与大模型在 B 端业务场景中的应用研发,覆盖 Prompt 工程、RAG、Agent 工作流编排、Function Calling / Tool Use 等关键链路。 (2)具体工作包括:意图理解与信息抽取、语义检索与排序优化、多轮对话与任务规划、Skill / Tool 设计与迭代、Badcase 分析与评测集建设。 (3)与工程、产品同学协同,推动算法效果在真实业务中跑通并持续优化。
包括英文材料
Transformer+
https://huggingface.co/learn/llm-course/en/chapter1/4
Breaking down how Large Language Models work, visualizing how data flows through.
https://poloclub.github.io/transformer-explainer/
An interactive visualization tool showing you how transformer models work in large language models (LLM) like GPT.
https://www.youtube.com/watch?v=wjZofJX0v4M
Breaking down how Large Language Models work, visualizing how data flows through.
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
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.
RAG+
https://www.youtube.com/watch?v=sVcwVQRHIc8
Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer.
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