美团大模型算法实习生
实习兼职核心本地商业-基础研发平台地点:北京状态:招聘
任职要求
1. 计算机科学、数学、统计学或相关领域的硕士或博士在读。 2. 熟悉Python、Java等至少一种编程语言与深度学习框架,具有良好的编程能力和扎实的数学理论基础。 3. 熟悉大模型的基本原理,具备精调、预训练、RLHF等方面的经验; 4. 关注行业前沿进展,对技术开发及应用有…
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工作职责
1. 探索LLM前沿领域研究,包括但不限于RAG、Agent、领域大模型、多模态融合等相关工作。 2. 通过微调/强化学习、预训练等技术方法,持续提高算法的效率和性能。 3. 参与LLM在搜索、对话系统等业务场景的应用。
包括英文材料
Python+
https://liaoxuefeng.com/books/python/introduction/index.html
中文,免费,零起点,完整示例,基于最新的Python 3版本。
https://www.learnpython.org/
a free interactive Python tutorial for people who want to learn Python, fast.
https://www.youtube.com/watch?v=K5KVEU3aaeQ
Master Python from scratch 🚀 No fluff—just clear, practical coding skills to kickstart your journey!
https://www.youtube.com/watch?v=rfscVS0vtbw
This course will give you a full introduction into all of the core concepts in python.
Java+
https://www.youtube.com/watch?v=eIrMbAQSU34
Master Java – a must-have language for software development, Android apps, and more! ☕️ This beginner-friendly course takes you from basics to real coding skills.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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
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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相关职位
实习网易有道
参与前沿大模型算法的研发与落地应用,方向包括但不限于:智能 Agent、Deep Research、多模态大模型、检索增强生成 (RAG) 等; 紧跟领域最新技术动态,探索创新算法方法,并积极推动科研成果的产出; 参与技术方案讨论、算法设计与实现、模型训练与优化等研发工作,保证项目进度和研发质量; 持续学习和掌握最新的大模型相关技术,并应用于实际产品和项目中,解决实际问题。
更新于 2025-06-18北京
实习内容理解
工作职责: 1. 真实业界数据的处理分析:定性分析、定量评估数据质量、对数据采集和处理方案不断优化改进; 2. 模型开发:参与Qwen、Llama等开源LLM的训练微调、量化和部署实践,追踪业内前沿,达到领先的性能指标; 3. 结合小红书丰富的工业场景,根据实际业务需求进行技术落地和创新。
更新于 2025-10-22北京