阿里巴巴算法技术- 视觉搜索任务中细粒度属性理解与应用-算法工程师实习生
实习兼职阿里巴巴研究型实习生地点:北京状态:招聘
工作描述
任职要求 1.计算机视觉和深度学习等相关专业,本科/硕士/博士; 2.具备扎实的计算机视觉/机器学习/深度学习理论功底和算法经验,或者在该领域有优秀的学术成果 (例如,主流会议CVPR/ICCV/ECCV/NeurIPS/ICLR等,发表过一作论文); 3.在计算机视觉领域有高影响力成果者优先,…
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.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
机器学习+
https://www.youtube.com/watch?v=0oyDqO8PjIg
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai.
https://www.youtube.com/watch?v=i_LwzRVP7bg
Learn Machine Learning in a way that is accessible to absolute beginners.
https://www.youtube.com/watch?v=NWONeJKn6kc
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
https://www.youtube.com/watch?v=PcbuKRNtCUc
Learn about all the most important concepts and terms related to machine learning and AI.
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/
CVPR+
https://cvpr.thecvf.com/
ICCV+
https://iccv.thecvf.com/
ICCV is the premier international computer vision event comprising the main conference and several co-located workshops and tutorials.
还有更多 •••
相关职位
实习阿里巴巴研究型实
1、计算机视觉和深度学习等相关专业,本科/硕士/博士; 2、具备扎实的计算机视觉/机器学习/深度学习理论功底和算法经验,或者在该领域有优秀的学术成果 (例如,主流会议CVPR/ICCV/ECCV/N
更新于 2026-03-20北京|杭州

社招1年以上技术类-算法
1、计算机、电子信息、数学等相关专业,硕士及以上学历; 2、有扎实的深度学习基础,对于常⻅的视觉感知识别任务(如⽬标检测、分割、跟踪)任⼀⽅⾯有深⼊理解,对于领域内的相关⽅案在实际中的效果深入理解。相
更新于 2026-04-08北京

社招3年以上技术类-算法
1. 深入理解 LLM/VLM 模型,熟悉主流 LLM/VLM 的模型结构和训练方法; 2. 熟悉大模型后训练技术,包括但不限于 SFT,RL 等技术,具备Qwen、Llama、Deepseek等模型
更新于 2026-04-08北京