美团机器人视觉算法专家
社招全职5年以上无人机业务部地点:北京状态:招聘
工作描述
任职要求 1.熟悉手部重建、关键点检测、多模态理解等计算机视觉领域的主流算法和研究进展,有相关项目经验者优先; 2.精通深度学习主流框架,具备模型训练、优化、部署全流程实战经验; 3.熟悉主流的SLAM、SFM框架,了解前馈式重建方法的原理和研究进展,具备相关项目经验和论文发表者优先; 4.具备良好的数据分析能力,熟悉数据标注流程及自动化标注系统的开发与应用; 5.具备利用AI技术解决复杂工程问题的能力,并能评估其在实际场景中的有效性与局限性; 6.熟练运用AI辅助工具(如代码生成、…
登录查看完整工作描述
微信扫码,1秒登录
包括英文材料
OpenCV+
https://learnopencv.com/getting-started-with-opencv/
At LearnOpenCV we are on a mission to educate the global workforce in computer vision and AI.
https://opencv.org/university/free-opencv-course/
This free OpenCV course will teach you how to manipulate images and videos, and detect objects and faces, among other exciting topics in just about 3 hours.
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
SLAM+
https://docs.mrpt.org/reference/latest/tutorial-slam-for-beginners-the-basics.html
[英文] SLAM for Dummies
https://dspace.mit.edu/bitstream/handle/1721.1/119149/16-412j-spring-2005/contents/projects/1aslam_blas_repo.pdf
A Tutorial Approach to Simultaneous Localization and Mapping
https://ouster.com/insights/blog/introduction-to-slam-simultaneous-localization-and-mapping
SLAM is an essential piece in robotics that helps robots to estimate their pose – the position and orientation – on the map while creating the map of the environment to carry out autonomous activities.
[英文] What Is SLAM?
https://www.mathworks.com/discovery/slam.html
How it works, types of SLAM algorithms, and getting started
数据分析+
[英文] Data Analyst Roadmap
https://roadmap.sh/data-analyst
Step by step guide to becoming an Data Analyst in 2025
还有更多 •••
相关职位

实习技术类
1. 有机械臂相关项目开发经验,有视觉伺服、机器人等开发经验优先 2. 熟悉至少一种协作机械臂品牌的SDK或控制接口 3. 熟悉视觉伺服算法(IBVS/PBVS)及手眼标定原理,熟练掌握ROS、Lua
更新于 2025-12-01杭州

社招算法研究
1. 本科及以上学历,计算机视觉、模式识别相关专业优先。 2. 精通OpenCV,PCL (Point Cloud Library)。 3. 熟悉主流3D检测与分割网络(PointNet++,Mask
更新于 2026-01-22北京
社招3年以上技术类-算法
1、硕士及以上,本科优秀者可考虑; 2、熟练 PCL / Open3D,扎实的点云处理基础; 3、熟悉点云/图像中的 物体检测、分类、实例分割 算法(传统方法及深度学习方法均可); 4、掌握至少一种6
更新于 2026-07-06杭州