Applied Scientist Intern, 2026 Shenzhen

Amazon Amazon · Big Tech · 44, China +1 · Applied Science

This internship focuses on bridging cutting-edge AI research with practical application and communication. The intern will translate complex AI concepts into understandable content for business stakeholders and the wider community, document AI capabilities, develop internal AI literacy programs, and contribute to applied research projects in NLP, Computer Vision, or Multimodal AI. The role requires a strong foundation in ML/DL, Python, and ML frameworks, with a passion for science communication and a curious, open mindset.

What you'd actually do

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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

Skills

Required

  • Master's or PhD in Computer Science, AI, Machine Learning, Statistics, or related quantitative field
  • Solid foundation in Machine Learning/Deep Learning (Transformer architectures, optimization algorithms, evaluation metrics, etc.)
  • Proficiency in Python and mainstream ML frameworks (PyTorch/TensorFlow/JAX)
  • Excellent communication skills: ability to explain gradient descent to a high school student or neural networks to a marketing manager
  • Demonstrated passion for 'science communication': whether through technical blogs, YouTube tutorials, academic tutoring, or open-source documentation
  • Curiosity-driven: open mindset to tolerate uncertainty and explore ambiguity in research

Nice to have

  • Published or submitted research papers and preprints (arXiv, academic conferences, etc.)
  • Experience explaining algorithms with visualization tools (e.g., D3.js, Manim, Observable)
  • Background in education, technical writing, or community management
  • Contributions to open-source ML projects
  • Existing portfolio of technical content (Medium column, personal blog, Bilibili/YouTube channel, WeChat official account articles, etc.)

What the JD emphasized

  • 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

Other signals

  • Translating complex AI concepts into understandable content
  • Documenting AI capabilities and limitations
  • Developing internal workshops or 'AI 101' courses
  • Outputting concise trend briefs on AI breakthroughs
  • Participating in end-to-end applied research projects
  • Literature review to prototype development
  • Natural Language Processing, Computer Vision, or Multimodal AI