intern machine learning Applied Scientist ic Master's · Posted Mar 26, 2026

About this role

Amazon is hiring a intern-level Applied Scientist in the machine learning function based in Shenzhen, China. The posting calls out experience with Python, TensorFlow, PyTorch. Listed education preference: a master's degree or equivalent.

Role
Applied Scientist
Function
machine learning
Level
intern
Track
Individual contributor
Employment
Internship
Location
Shenzhen, China
Work mode
On-site
Education
Master's degree
Department
Applied Science
Posted
Mar 26, 2026
AI Summary
Applied Scientist intern bridging AI research and business communication. Translate complex ML concepts into accessible content, participate in end-to-end research projects spanning NLP, computer vision, and multimodal AI. Requires strong ML/deep learning fundamentals, Python proficiency, and exceptional communication skills.

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Job description

from Amazon careers
职位:Applied scientist 应用科学家实习生
毕业时间:2026年10月 - 2027年7月之间毕业的应届毕业生
· 入职日期:2026年6月及之前
· 实习时间:保证一周实习4-5天全职实习,至少持续3个月
· 工作地点:深圳福田区

投递须知:
1 填写简历申请时,请把必填和非必填项都填写完整。提交简历之后就无法修改了哦!
2 学校的英文全称请准确填写。中英文对应表请查这里(无法浏览请登录后浏览)https://docs.qq.com/sheet/DVmdaa1BCV0RBbnlR?tab=BB08J2

关于职位
Amazon Device &Services Asia团队正在寻找一位充满好奇心、善于沟通的应用科学家实习生,成为连接前沿AI研究与现实世界认知的桥梁。这是一个独特的角色——既需要动手参与机器学习项目,又要接受将复杂AI概念转化为通俗易懂内容的创意挑战。D&S Asia是亚马逊设备与服务业务在亚洲的支柱组织,自2009年支持Kindle制造起步,现已发展为横跨软硬件、AI(Alexa)及智能家居(Ring/Blink)的综合性团队,持续驱动区域业务创新与人才发展。

你将做什么
• 解密AI: 将复杂的技术发现转化为直观的解释、博客文章、教程或互动演示,让非技术背景的业务方和更广泛的社区都能理解
• 技术叙事: 与工程团队协作,以清晰、引人入胜的方式记录AI的能力与局限性
• 知识共享: 协助开发内部工作坊或"AI入门"课程,提升跨职能团队(产品、设计、商务)的AI素养
• 保持前沿: 持续学习并整合最新突破(如大语言模型、扩散模型、智能体),为团队输出简明易懂的趋势简报
• 研究与应用: 参与端到端的应用研究项目,从文献综述到原型开发,涵盖自然语言处理、计算机视觉或多模态AI领域

Basic Qualifications

- 正在攻读计算机科学、人工智能、机器学习、统计学或相关定量领域的硕士或博士学位
- 扎实的机器学习/深度学习基础(Transformer架构、优化算法、评估指标等)
- 精通Python及主流机器学习框架(PyTorch/TensorFlow/JAX)
- 卓越的沟通能力: 能够向高中生解释清楚梯度下降,或向市场经理讲明白神经网络
- 对"科学传播"有实证热忱: 无论是通过技术博客、YouTube教程、学术辅导还是开源文档
- 好奇心驱动: 具备在研究中容忍不确定性、在模糊中探索的开放心态

Preferred Qualifications

- 已发表或在投的研究论文及预印本(arXiv、学术研讨会等)
- 使用可视化工具解释算法的经验(如D3.js、Manim、Observable)
- 教育、技术写作或社区运营背景
- 对开源机器学习项目的贡献
- 现有技术内容作品集(Medium专栏、个人博客、B站/YouTube频道、微信公众号文章等)

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