高德地图高德-资深VLA/空间计算/强化学习算法专家-视觉团队
社招全职3年以上技术类-算法地点:北京状态:招聘
任职要求
● 计算机科学、人工智能、机器人、电子工程等相关专业硕士及以上学历; ● 5年及以上自动驾驶/服务机器人领域核心算法经验,主导自动驾驶/机器人领域核心算法量产落地; ● 具备扎实的算法和编程基础,熟练使用至少一种深度学习框架; ● 在计算机视觉、自然语言处理、机器人感知或强化学习等领域有研究或项目经验; ● 在顶级会议(CVPR、ICCV、ECCV、NeurIPS、ICML、ICLR、IROS、RSS、CoRL等)发表过论文者优先。 技术方向加分项(满足至少一个方向): ● 视觉-语言-动作方向:熟悉 Vision-Language Pre-training、具身智能(Embodied AI)、模仿学习、多模态决策系统等,有实际部署经验加分; ● 空间计算方向:熟悉 SLAM(视觉/激光/多传感器融合)、三维重建(3DGS、NeRF、Mesh)、点云处理、几何优化等; ● 强化学习方向:熟悉深度强化学习(GRPO、DQN、A3C、PPO、SAC等)、多智能体RL等,有Isaac、Mujoco等仿真环境开发经验加分; 我们提供: ● 与世界一流AI科学家和工程师共事的机会; ● 参与高德地图核心产品和技术演进,影响亿万用户; ● 宽广的技术成长空间与自由探索氛围; ● 具有竞争力的薪酬福利体系。
工作职责
我们正在寻找在具身智能VLA(视觉-语言-动作)、空间计算(重建、SLAM等)及强化学习领域有深厚积累的算法同学,加入高德地图视觉技术中心。你将参与构建下一代地图中的感知、理解与决策系统,推动具身导航、AR/VR、场景建模等前沿技术的研发与落地。 如果你热衷于用AI改变人们出行方式,渴望在真实世界大规模数据上验证算法能力,欢迎加入我们! 岗位职责: ● 负责视觉语言动作(VLA)的具身智能模型和视觉语言模型(VLM)的研发,提升具身agent的空间理解和行动决策能力; ● 推进空间计算相关技术(如SLAM、三维重建、点云处理、姿态估计等)在下一代地图、虚拟现实等场景的应用; ● 探索强化学习在多模态大模型的后训练中的应用,提升具身/空间智能的能力天花板; ● 跟踪国际前沿技术发展,持续推动技术创新,并落实到实际应用中; ● 与工程团队紧密协作,完成从算法研发到系统部署的全流程闭环。
包括英文材料
学历+
自动驾驶+
https://www.youtube.com/watch?v=_q4WUxgwDeg&list=PL05umP7R6ij321zzKXK6XCQXAaaYjQbzr
Lecture: Self-Driving Cars (Prof. Andreas Geiger, University of Tübingen)
https://www.youtube.com/watch?v=NkI9ia2cLhc&list=PLB0Tybl0UNfYoJE7ZwsBQoDIG4YN9ptyY
You will learn to make a self-driving car simulation by implementing every component one by one. I will teach you how to implement the car driving mechanics, how to define the environment, how to simulate some sensors, how to detect collisions and how to make the car control itself using a neural network.
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.
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.
NLP+
https://www.youtube.com/watch?v=fNxaJsNG3-s&list=PLQY2H8rRoyvzDbLUZkbudP-MFQZwNmU4S
Welcome to Zero to Hero for Natural Language Processing using TensorFlow!
https://www.youtube.com/watch?v=R-AG4-qZs1A&list=PLeo1K3hjS3uuvuAXhYjV2lMEShq2UYSwX
Natural Language Processing tutorial for beginners series in Python.
https://www.youtube.com/watch?v=rmVRLeJRkl4&list=PLoROMvodv4rMFqRtEuo6SGjY4XbRIVRd4
The foundations of the effective modern methods for deep learning applied to NLP.
强化学习+
https://cloud.google.com/discover/what-is-reinforcement-learning?hl=en
Reinforcement learning (RL) is a type of machine learning where an "agent" learns optimal behavior through interaction with its environment.
https://huggingface.co/learn/deep-rl-course/unit0/introduction
This course will teach you about Deep Reinforcement Learning from beginner to expert. It’s completely free and open-source!
https://www.kaggle.com/learn/intro-to-game-ai-and-reinforcement-learning
Build your own video game bots, using classic and cutting-edge algorithms.
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.
ECCV+
https://eccv.ecva.net/
ECCV is the official event under the European Computer Vision Association and is biannual on even numbered years.
NeurIPS+
https://neurips.cc/
ICML+
https://icml.cc/
ICLR+
https://iclr.cc/
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
智能体+
https://learn.microsoft.com/en-us/shows/ai-agents-for-beginners/
In this 10-lesson course we take you from concept to code while covering the fundamentals of building AI agents.
https://www.ibm.com/think/ai-agents
Your one-stop resource for gaining in-depth knowledge and hands-on applications of AI agents.
相关职位
社招3年以上A181440A
1、主导或参与机器人相关仿真/训练/AIGC/渲染中一个或多个方向的技术架构设计与开发,与产品协作实现业务目标; 2、与产品//销售/市场团队紧密协作,制定技术方案并推动落地,持续优化系统架构与用户体验; 3、独立完成项目需要的系统分析、设计,编码,测试和上线部署任务,确保项目的进度、质量和稳定性要求; 4、有一定的技术前瞻性,可以对平台演进中的技术需求(如机器人仿真数据生产加速)进行预研和设计,满足对各项业务场景的客户需求。
更新于 2025-04-03
社招
- 研究和开发基于强化学习的自动驾驶决策规划模型,提升自动驾驶系统的安全性、舒适性和效率; - 与感知、规划、VLM/VLA 等模块紧密合作,设计和实现自动驾驶大规模强化学习训练框架; - 跟踪强化学习领域最新进展,并将先进技术应用于实际产品中,实现AI技术的商业化交付。
更新于 2025-02-12