小红书急招-iOS开发工程师-AI 创新应用(社区)
社招全职3-5年客户端开发地点:北京 | 上海状态:招聘
任职要求
1、以 AI Coding 为核心驱动,从 0 到 1 研发独立 App,探索并打造“AI Native”产品形态。 2、基于真实用户需求,结合大模型/多模态能力,设计并实现行业领先的用户体验与功能闭环。 3、构建高质量代码与架构,沉淀优秀设计理念,主导核心模块与难点问题的技术攻坚与性能优化。 4、设计并实现易用且高效的 Agent 开发配套工具/套件,提升研发效率,降低 Agent 技术的使用门槛,并保障交付质量与一致性。 加分项: 1、有 Core ML、TensorFlow Lite、PyTorch Mobile 或端侧推理加速(Metal/BNNS)实践。 2、有灰度发布、A/B 实验、可观测性(Logging/Tracing/指标)与质量基线(SLI/SLO)建设经验。 3、有开源项目、技术博客或技术演讲产出。
工作职责
1、本科及以上学历,计算机或相关专业;1年及以上客户端(iOS/跨端优先)研发经验。 2、熟悉主流 App 框架与开发模式(Swift/SwiftUI/UIKit;MVVM/VIPER 等),有独立 App 从 0-1 上线经验者优先。 3、精通性能分析与优化,包括内存占用、耗电、网络、启动速度、UI 渲染与卡顿治理(Instruments 等)。 4、至少熟悉一种 AI Coding 工具或工作流(如 Cursor、Claude、Copilot、Codeium 等),能将其有效融入日常研发与评审流程。 5、具备强烈的技术好奇心与自驱力,优秀的问题分解与抽象能力,善于在不确定性中快速推进。 6、有 Agent 框架/工具链(如 LangChain、AutoGen、OpenAI Assistants 或自研)的设计与实践经验者优先;具备提示工程、工具调用、工作流编排与质量保障经验更佳。
包括英文材料
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
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.
Core ML+
[英文] Getting Started
https://apple.github.io/coremltools/docs-guides/source/introductory-quickstart.html
Core ML Tools can convert trained models from other frameworks into an in-memory representation of the Core ML model.
https://developer.apple.com/machine-learning/core-ml/
Core ML is optimized for on-device performance of a broad variety of model types by leveraging Apple silicon and minimizing memory footprint and power consumption.
https://www.youtube.com/watch?v=g3yj9_DHrME
Bring the power of machine learning directly to your apps with Core ML.
TensorFlow+
https://www.youtube.com/watch?v=tpCFfeUEGs8
Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you’ve come to the right place.
https://www.youtube.com/watch?v=ZUKz4125WNI
This part continues right where part one left off so get that Google Colab window open and get ready to write plenty more TensorFlow code.
PyTorch Mobile+
https://towardsdatascience.com/deep-learning-on-your-phone-pytorch-lite-interpreter-for-mobile-platforms-ae73d0b17eaa/
The PyTorch Deep Learning framework supports seamlessly running server trained CNN and other ML models on mobile devices.
https://www.python-engineer.com/posts/pytorch-ios-app/
Learn how to deploy PyTorch models on iOS devices with Torchscript.
https://www.youtube.com/watch?v=O_2KBhkIvnc
Running ML on edge devices is growing in importance as applications continue to demand lower latency.
https://www.youtube.com/watch?v=Qb4vDm-ruwI
PyTorch Mobile provides a runtime environment to execute state-of-the-art machine learning models on mobile devices.
Metal+
[英文] Metal
https://developer.apple.com/metal/
Whether you want to build a graphics-intensive app, a cutting-edge game with beautiful visuals, or target demanding compute workloads like machine learning, Metal puts the advanced capabilities of Apple-designed GPUs at your fingertips.
[英文] Metal Tutorial
https://metaltutorial.com/
This tutorial will teach you the basics of Apple's Metal Graphics and Compute API, and help you understand how to program with it in C++ via the metal-cpp library.
https://www.kodeco.com/7475-metal-tutorial-getting-started
In this Metal tutorial, you will learn how to get started with Apple’s 3D graphics API by rendering a simple triangle to the screen.
[英文] learnmetal.com: Home
https://www.learnmetal.com/
Welcome to Learn Metal — an open-source tutorial site focused on learning and mastering Apple’s Metal graphics API.
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