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Open nowPosted 57 days ago

算法工程化软件开发

agirobot/internrecruitment367 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now算法工程化软件开发agirobot/internrecruitment · Beijing, Chinese Mainland

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on agirobot/internrecruitment's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. agirobot/internrecruitment postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 57 days ago

agirobot/internrecruitment median: 2 days open

The posting

1. 算法集成框架开发 - 参与机器人算法集成框架的设计与开发，抽象模型加载、内存管理、张量传递、多模型调度、前后处理等通用能力，让算法模块以标准化方式接入机器人系统。 - 打通「模型训练产出 → 模型转换/量化 → 推理引擎 → 机器人本体运行」的完整链路，降低算法上车的工程成本。

2. 端侧部署与极致性能优化 - 面向端侧计算平台（GPU / NPU / SoC）完成模型部署，围绕延迟、吞吐、显存占用、功耗做端到端优化。 - 使用 CUDA 等手段编写与优化高性能算子，进行算子融合、内存复用、零拷贝、流水并行、多流并发等优化。 - 实践量化、剪枝、蒸馏、图优化等模型压缩与加速方法，在精度可控的前提下换取性能收益。

3. 性能分析与工具建设 - 使用 Nsight Systems / Nsight Compute、perf 等工具做性能剖析，定位算子级与系统级瓶颈。 - 参与 Profiler、Benchmark、精度对齐与回归测试工具链的建设，让性能与精度变化可量化、可追溯。

4. 协同与落地 - 与算法团队协作完成模型上车前的工程适配，与嵌入式/系统团队协作解决跨层性能问题，把优化经验沉淀为框架能力和文档。

技术背景要求

  • 在读本科/硕士/博士，计算机、软件工程、自动化、电子信息、人工智能等相关专业；每周可实习 4 天以上，可连续实习 3 个月以上。
  • 熟悉 C++：掌握 C++11/14/17 常用特性，理解内存模型、指针与生命周期管理、多线程与并发，有良好的工程编码习惯。
  • 熟悉 Python：能独立完成脚本开发、模型转换与验证、自动化工具编写。
  • 熟悉 CUDA：理解 GPU 编程模型（线程/线程块/warp、global/shared memory、访存合并等），能读写并调试 CUDA Kernel，理解性能瓶颈的常见来源。
  • 熟悉 Linux 开发环境，掌握 Git、CMake 等基础工程工具。
  • 对性能优化有兴趣和敏感度，愿意通过数据（而不是猜测）定位问题。
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