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lxl0928/README.md

李小龙 | Li Xiaolong

8年云平台研发与技术管理经验 | AI视觉云原生架构负责人

Backend R&D Engineer / Machine Vision Cloud Platform Tech Lead

📍 Location:Haidian District, Beijing

📱 Phone:176-XXXX-XXXX

📧 Email:timilong928@gmail.com

👋 关于我 | About Me

拥有 8 年云平台研发与技术管理经验,现任机器视觉云平台技术负责人,带领 10 人研发团队长期深耕视觉算法工程化、大规模视频流媒体系统、分布式 AI 推理平台架构设计与性能调优;近年主攻大模型应用、RAG 向量检索,独立完成从 0 到 1 的智能检索服务搭建。擅长结合云原生分布式技术实现 AI 视觉业务规模化落地,平衡技术深度与商业价值,长期聚焦多模态大模型 + 智能搜索赛道。

8 years of experience in cloud platform R&D and technical management. Currently serving as the technical lead of a machine vision cloud platform, leading a 10-member R&D team specialized in visual algorithm engineering, large-scale video streaming systems, and distributed AI inference platform architecture design & performance optimization. Recent focus: LLM applications and RAG vector retrieval; independently built an intelligent search service from scratch. Skilled at scaling multimodal AI vision businesses with cloud-native distributed architecture, balancing technical depth with commercial value.

🎓 教育背景 | Education

湖南大学 | Hunan University

2015.09 - 2017.07 | 软件工程 本科 | Bachelor of Software Engineering

  • GPA:3.7/4.0,专业排名前 1% | Top 1% of major

西南民族大学 | Southwest Minzu University

2013.09 - 2015.07 | 软件工程(湖大联合培养)| Joint Training Program with Hunan University

  • GPA:3.6,专业排名 1%~5% | Top 1%~5% of major
  • 2015 全国大学生计算机设计大赛 省一等奖、全国二等奖 | 2015 China Collegiate Computing Competition: Provincial First Prize, National Second Prize

💼 工作经历 | Work Experience

北京升哲科技 | SENSORO

机器视觉平台组负责人 | Tech Lead, Machine Vision Platform

2018.07 - Present

  1. 搭建并管理一支涵盖前后端与流媒体的 10 人完整研发团队,统筹团队人才建设、任务排期与技术管理;
  2. 全面负责智慧城市 AI 云平台整体方案设计与技术攻坚,统筹视觉算法工程化、云平台架构、软硬件一体化产品研发与商业化落地;
  3. 保障多个大型政府智慧城市项目高质量交付,支撑多条 AI 视觉业务线规模化落地。

上海数巧信息科技 | Simright

后端工程师 | Backend Engineer 2017.05 - 2018.05

  1. 独立负责云端 CAE 仿真平台、协同研发系统的后端架构开发;
  2. 承担业务服务编码、分布式任务调度、线上运维体系搭建;
  3. 支撑工业仿真软件云端化转型与企业客户落地交付。

🚀 核心项目:智慧城市社会治理 AI 视觉云平台 | Core Project

Role:机器视觉云平台负责人 | Duration:2019.08 - 2026.07

从 0 到 1 搭建整套 AI 视觉产品体系,完成多地市级智慧城市项目的规模化商用落地。

1. 技术架构 | Tech Architecture

基于 Python / FastAPI / Tornado 构建全栈分布式云原生平台,核心技术栈:

  • 中间件:Kafka、Redis、Celery、Nacos
  • 存储:PostgreSQL、Elasticsearch、Milvus/Zilliz 向量库、S3 对象存储
  • 容器编排:Docker、K8s
  • 视觉模型:YOLO、ResNet、Transformer 多模态视觉模型

自研五大核心引擎:

  • MLS 算法推理引擎 | Algorithm Inference Engine
  • AISE 视图结构化引擎 | Image & Video Structuring Engine
  • VS2C 云智能解析引擎 | Cloud Video Analysis Engine
  • DMS 全生命周期数据平台 | Full-Lifecycle Data Management Platform
  • IVMS 视频综合管理平台 | Integrated Video Management Platform

2. 商业成果 | Business Achievements

落地数字点军、数智五峰、宜昌算力中心、川南人工智能算力中心等政府标杆项目。

  • 项目累计中标总额超 5 亿元,全部按期验收交付

3. 平台承载规模 | Platform Scale

  • 接入自研智能摄像机 15000+ 台,存量视频流 30000+ 路
  • 稳定承载同时在线实时视频流 40000+ 路

4. 核心性能指标 | Core Performance

  • 人脸/人体/车辆实时结构化:6000+ QPS,平均响应 ≤ 100ms
  • 人员聚档、身份还原向量检索:1000+ QPS,平均响应 ≤ 150ms

🛠 技术栈 | Tech Stack

Backend & Cloud Native

Python, FastAPI, Tornado, Docker, K8s, Microservices, Nacos, Celery

Distributed Middleware & Database

Kafka, Redis, Elasticsearch, Milvus/Zilliz, PostgreSQL, S3 / MinIO

Computer Vision & AI Inference

YOLO, ResNet, Transformer, Video Stream Parsing, Model Performance Tuning

LLM & RAG

Vector Retrieval System, Intelligent Search Service, LLM Engineering & Productionization

DevOps & O&M

Distributed Task Scheduling, High Concurrency Optimization, Large-scale Video Cluster Operations

🏆 获奖经历 | Honors & Awards

职场荣誉 | Professional Honors

  • SENSORO 优秀员工(2019/2020/2021)连续三年获评,表彰项目攻坚、团队建设与业务落地突出贡献

校园竞赛 | Academic Competition

  • 2015 中国大学生计算机设计大赛
    • 四川省一等奖 | Sichuan Provincial First Prize
    • 全国总决赛二等奖 | National Finals Second Prize

🎯 职业发展方向 | Career Development Direction

深耕大模型多模态应用开发、RAG 向量检索、智能搜索、Agent 开发、大规模云原生 AI 推理平台架构方向;持续拓展机器视觉与大模型的融合落地场景。

Focus on multimodal LLM application development, RAG vector retrieval, intelligent search, Agent development, and large-scale cloud-native AI inference platform architecture; continue exploring fusion scenarios of computer vision and large language models.

📬 联系方式 | Contact

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