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Open nowPosted 69 days ago

智能硬件-端侧 AI 部署与应用工程师 (2027届校招)

thundersoft/campus141 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now智能硬件-端侧 AI 部署与应用工程师 (2027届校招)thundersoft/campus · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. thundersoft/campus postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.7%14 days
  5. 35.6%30 days
  6. 58.0%60 days
This job: posted 69 days ago

thundersoft/campus median: 1 days open

The posting

你将加入我们的核心研发团队，基于Qualcomm计算平台，打通从 AI 模型到端侧应用落地的“最后一公里”。我们需要你不仅懂算法原理，更能通过扎实的工程能力，构建高性能的 AI Agent 与推理系统。 1. 模型转换与性能调优 (Model Engineering): 使用 Linux 环境下的工具链，将 PyTorch/TensorFlow 训练模型转换为专用格式（DLC/QNN context）。 编写 Shell/Python 脚本 实现模型转换、量化（Int8/FP16）及精度验证的自动化流程。 分析模型在 Hexagon DSP/NPU 上的性能瓶颈，进行算子优化和推理加速。 2. 端侧 AI 系统开发 (System Integration): 基于 Android/Linux 系统，使用 C++ 开发高性能 AI 推理引擎及业务逻辑。 利用 Docker 维护统一的交叉编译与开发环境，确保 SDK 版本的一致性。 参与 AI Agent（智能体）的工程化实现，包括端侧 LLM 接入、工具链调用（Tool Use）及多模态数据流处理。 3. 代码与版本管理 (Engineering Excellence): 严格遵循代码规范，使用 Git 进行代码版本控制、分支管理和协同开发。 编写清晰的技术文档，记录模型转换参数与优化路径。

1. 核心编程能力 (The Must-Haves): 学历专业： 统招985/理工类211/QS前100 本科及以上学历，计算机、电子、自动化等相关专业。 C++ 基础： 熟练掌握 C/C++，理解指针、内存管理、多线程编程（这是端侧部署的基石）。 Python 能力：能熟练编写 Python 脚本进行数据处理和模型胶水代码开发。 2. 工程与系统素养 (Engineering Foundation): Linux/Shell：熟悉 Linux 开发环境（Ubuntu/CentOS），熟练使用命令行工具，能编写 Shell (Bash) 脚本 自动化处理日常任务。 工具链： 熟悉 Git 的基本操作（clone, commit, push, merge, resolve conflicts），有团队协作意识。 容器化：了解 Docker 的基本原理与常用命令，有使用 Docker 搭建开发环境的经验者优先。 3. AI 理论基础: 理解 CNN、Transformer 的基本结构，熟悉至少一种主流框架（PyTorch/TensorFlow）。 了解模型量化（Quantization）的基本概念（如 Int8 vs FP32）。 4. 软素质: 具备极强的自驱力和动手能力。 良好的英语阅读能力，能无障碍阅读英文技术文档。 【加分项】（有以下任意一项经历将极具竞争力） 高通/端侧经验： 接触过 SNPE, QNN, TFLite, ONNX Runtime, MNN 等端侧推理框架。 工程构建： 熟悉 CMake / Makefile 构建系统；或者了解 Android NDK 开发。 Agent 实践： 玩过 LangChain，或者在本地部署过 Llama/ChatGLM 等大模型。 CI/CD： 了解持续集成流程（如 GitHub Actions, Jenkins）的基本概念。

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