蔚来人工智能应用专家—测试场景
社招全职3-5年数字技术地点:上海状态:招聘
任职要求
- 人工智能、机器人、多模态大模型等相关领域的硕士或博士; - 熟悉机器人感知系统(深度相机、单目/双目视觉等SLAM)原理和算法; - 熟悉多自由度机器人(双足、四足、灵巧手)模仿学习、强化学习算法设计与仿真,具有sim to real经验者优先; - 熟悉Transformer结构,了解R3M、RFM、PaLM-E等多模态具身大模型经验者优先; - 有良好的创新想法和工程能力; - 优秀的分析的解决问题能力,具备良好的团队协作素质。 - 具有强化学习和Sim to real经验者优先 - 参与过多自由度机器人研发、调优经验者优先
工作职责
- 结合测试业务需求,对机器人产品(双足、四足、灵巧手)进行选型、设计与集成; - 开发/应用机器人感知系统和运动控制系统,落地基础能力:环境建图、目标识别、轨迹规划等; - 针对测试对象,开发/应用通用型具身算法,实现物体泛化、任务泛化能力; - 研究多模态具身大模型,实现机器人对复杂测试任务的分解,及和物理世界的交互(视觉、触觉、语音等); - 追踪行业动态,对进行评测和落地,持续优化应用;
包括英文材料
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
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
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/
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.
Transformer+
https://huggingface.co/learn/llm-course/en/chapter1/4
Breaking down how Large Language Models work, visualizing how data flows through.
https://poloclub.github.io/transformer-explainer/
An interactive visualization tool showing you how transformer models work in large language models (LLM) like GPT.
https://www.youtube.com/watch?v=wjZofJX0v4M
Breaking down how Large Language Models work, visualizing how data flows through.
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