美团【转正实习】自动驾驶算法工程师
实习兼职自动车配送部地点:北京 | 深圳状态:招聘
任职要求
1.计算机或相关专业本科及以上学历; 2.扎实的计算机理论基础; 3.优秀的算法和数据结构能力; 4.熟练掌握至少一门主流开发语言,能编写高效且易读的代码; 5.强烈的责任心和工作积极性。 具备以下经验者优先 1.NOI、ACM获奖经历或其他能证明学习能力的亮眼成果; 2.在相关领域如计算机视觉、激光处理算法、机器学习、SLAM、操作系统、机器人等领域发表高质量论文; 3.有参与大型开源项目的经验。
工作职责
1.如果你对于精准识别自动配送车周围的环境状态感兴趣,你可以参与到环境感知的算法研发; 2.如果你对于预测自动配送车周围障碍物意图和行为感兴趣,你可以参与到障碍物预测的算法研发; 3.如果你对于精确制定并完成自动配送车的行驶轨迹感兴趣,你可以参与到决策规划与控制的算法研发; 4.如果你对于精细刻画自动配送车行驶区域内的环境及精确定位感兴趣,你可以参与到高精地图的自动化元素提取、建图与更新以及定位算法研发; 5.如果你对于综合各类传感器数据并得到精确结果感兴趣,你可以参与到传感器融合的算法研发。
包括英文材料
学历+
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/
数据结构+
https://www.youtube.com/watch?v=8hly31xKli0
In this course you will learn about algorithms and data structures, two of the fundamental topics in computer science.
https://www.youtube.com/watch?v=B31LgI4Y4DQ
Learn about data structures in this comprehensive course. We will be implementing these data structures in C or C++.
https://www.youtube.com/watch?v=CBYHwZcbD-s
Data Structures and Algorithms full course tutorial java
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.
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.
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
相关职位

实习技术
1. 协助研发基于强化学习(RL)或模仿学习(IL)的自动驾驶决策规划算法,解决复杂交通场景下的车辆行为决策与运动规划问题; 2. 参与构建和优化用于训练决策模型的数据处理流程,包括特征工程、场景提取、奖励函数设计及大规模数据集处理; 3. 负责或参与相关算法的仿真测试、实车调试、性能评估与迭代优化,推动算法在真实环境中的性能提升和落地; 4. 跟踪并调研强化学习、模仿学习、行为预测等领域的国际前沿动态与最新研究成果(如顶会论文CVPR, ICRA, NeurIPS, ICML等),并尝试将其应用于实际项目; 5. 协助端到端自动驾驶大模型或相关子模块的研发与优化工作。
更新于 2025-09-08
实习自动车配送部
1.负责机器人导航定位算法研发,包括卫星导航、视觉或激光SLAM、组合导航; 2.负责机器人视觉建图与渲染、全局视觉定位算法研发,包括视觉特征检测与匹配、相机姿态估计、多视几何重建、稠密点云重建、神经场渲染; 3.负责机器人控制、规划与调度算法研发; 4.负责机器人算法在嵌入式平台加速与优化; 5.负责机器人无线通信算法研发;6.负责机器人电机驱动算法研发; 7.负责低空物流无人配送领域机器学习、数据挖掘、仿真建模算法研发。
更新于 2025-02-26

实习技术
工作职责: 1. 算法开发与验证:参与结构化/非结构化道路的决策规划算法设计与开发,包粗轨迹生成、决策体系搭建,并通过仿真或实车测试验证算法效果; 2. 问题分析与闭环:协助分析道路测试数据,定位决策逻辑或规划轨迹的异常根因,提出优化方案并参与代码实现,提升算法鲁棒性; 3. 工具链支持:开发或优化调试工具链(可视化工具等),支持算法快速迭代与效果追踪。
更新于 2025-09-01