蔚来校招-大模型数据闭环算法工程师
校招全职算法地点:上海 | 北京状态:招聘
任职要求
你需要在以下一个或多个领域拥有扎实的专业知识和经验: 1. 拥有国内外知名大学计算机、电子工程,人工智能、物理、数学,汽车等密切相关领域的硕士、博士学位(优先) 2. 扎实的计算机基础,在以下一个或多个领域拥有专业知识和研究成果:机器学习、深度学习、强化学习、智能辅助驾驶、机器人技术等 3. 拥有较强的问题解决能力和编程技能,熟练使用Python(必需)和C++(优先),并将编码最佳实践作为工作的一部分 4. 拥有良好积极的沟通能力和团队合作精神 加分项: 1. 熟悉多模态大模型(VLM)的微调(SFT/RL)方法,有相关实践经验 2. 熟悉常见的端到端智能辅助驾驶算法(CaRL,Diffusion Planner,PLUTO, PlanTF, PlanT, Think2Drive 等) 3. 熟悉Carla,nuplan,metadrive等常见的仿真强化学习环境,有相关实践经验 4. 在主要会议(RSS、ICRA、CoRL、CVPR、ICLR、ICML、NeurIPS、ICCV、AAAI等)上发表的研究论文
工作职责
1. 负责将多模态大语言模型(VLM)应用在车辆场景理解和corner case挖掘的工作中,完成数据挖掘交付任务 2. 负责利用规则挖掘的数据冷启动多模态大语言模型,规则+模型,提高数据挖掘效率 3. 与基础设施团队合作,构建高效的数据、训练、评估和标注流程
包括英文材料
学历+
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.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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.
Python+
https://liaoxuefeng.com/books/python/introduction/index.html
中文,免费,零起点,完整示例,基于最新的Python 3版本。
https://www.learnpython.org/
a free interactive Python tutorial for people who want to learn Python, fast.
https://www.youtube.com/watch?v=K5KVEU3aaeQ
Master Python from scratch 🚀 No fluff—just clear, practical coding skills to kickstart your journey!
https://www.youtube.com/watch?v=rfscVS0vtbw
This course will give you a full introduction into all of the core concepts in python.
C+++
https://www.learncpp.com/
LearnCpp.com is a free website devoted to teaching you how to program in modern C++.
https://www.youtube.com/watch?v=ZzaPdXTrSb8
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
SFT+
https://cameronrwolfe.substack.com/p/understanding-and-using-supervised
Understanding how SFT works from the idea to a working implementation...
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/
ICLR+
https://iclr.cc/
ICML+
https://icml.cc/
NeurIPS+
https://neurips.cc/
ICCV+
https://iccv.thecvf.com/
ICCV is the premier international computer vision event comprising the main conference and several co-located workshops and tutorials.
相关职位

校招算法序列
1、负责训练评测数据特征仓库建设、相关指标实现; 2、 负责训练评测数据交付,保证数据质量; 3、 负责端到端智驾数据产线基础工具链建设、训练评测数据业务流程建设;
更新于 2025-07-04
校招
1. 算法开发与优化: 负责自动驾驶模型算法的研发设计,包括但不限于行为决策、轨迹生成、运动规划等模块的深度学习/强化学习模型设计 探索基于Transformer、模仿学习(Imitation Learning)、强化学习(RL)等前沿技术的模型算法设计、应用方案 优化自动驾驶算法的实时性、安全性和舒适性,解决复杂场景(如拥堵、交互博弈、长尾问题)下的规划挑战 2.数据驱动迭代: 构建和利用大规模驾驶数据集(仿真+真实数据),设计数据闭环 pipeline 提升规划性能 参与数据标注、场景挖掘、仿真测试等环节,推动算法迭代 3.系统集成与部署: 与感知、控制等模块团队协作,实现模型算法在车载计算平台的部署 支持实车测试,分析问题并提出改进方案 4.前沿技术跟踪: 跟进学术界(如CVPR、ICRA、CoRL、IROS等)和工业界最新进展,将创新技术落地到量产或研发项目中
更新于 2025-07-01

校招算法序列
1、负责自动驾驶领域中基于学习的预测、规划、决策及端到端等任务的数据交付工作。 2、构建数据挖掘、数据分布管理及数据版本迭代的工程体系,保障模型持续优化及实车问题的有效解决。 3、推动高效的模型闭环迭代流程建设,深入优化流程效率与交付质量。
更新于 2025-07-04