理想汽车【自动驾驶】高级端到端算法工程师
社招全职3年以上自动驾驶地点:北京状态:招聘
任职要求
1. 有3年以上自动驾驶研发经验,熟悉自动驾驶感知/预测/决策规划方法,有端到端研发和部署经验者优先; 2. 应用数学、模式识别、机器学习、电子信息、机器人等相关专业业的硕士/博士或者同等工作经验; 3. 熟悉当前主流的深度学习算法,精通一个或多个领域算法研究,包括但不限于目标检测、图神经网络、NLP、大模型等领域; 4. 深入了解数据结构、算法、并行编程、代码优化和大规模数据处理等相关知识;至少精通C/C++或Python编程,有ACM经验者优先; 5. 有计算机视觉及模式识别领域顶会(CVPR/ICCV/ECCV/ICML/NeurIPS)或顶刊(TPAMI/IJCV/TIP)者优先;有顶级学术比赛成果或实际工程项目经验者优先。
工作职责
1. 负责理想汽车自动驾驶端到端模型方法研发和工程落地,包括但不限于动静态感知/通用障碍物/障碍物预测决策等端到端模型; 2. 负责设计高性能上限,具备量产能力的端到端模型算法,包括但不限于diffusion、VLM等模型算法; 3. 开发高效离线训练框架,以及可实时运行的在线推理框架,优化模型推理性能,研发模型部署工具链和优化工具; 4. 建立云端数据感知/决策联合标注Pipeline、数据挖掘机制以及难样本分析等工具链,利用影子模型挖掘众包数据,通过数据闭环持续选代模型能力。
包括英文材料
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.
模式识别+
https://www.mathworks.com/discovery/pattern-recognition.html
Pattern recognition is the process of classifying input data into objects, classes, or categories using computer algorithms based on key features or regularities.
https://www.microsoft.com/en-us/research/wp-content/uploads/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf
Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science.
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.
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/
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.
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
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
C+
https://www.freecodecamp.org/chinese/news/the-c-beginners-handbook/
本手册遵循二八定律。你将在 20% 的时间内学习 80% 的 C 编程语言。
https://www.youtube.com/watch?v=87SH2Cn0s9A
https://www.youtube.com/watch?v=KJgsSFOSQv0
This course will give you a full introduction into all of the core concepts in the C programming language.
https://www.youtube.com/watch?v=PaPN51Mm5qQ
In this complete C programming course, Dr. Charles Severance (aka Dr. Chuck) will help you understand computer architecture and low-level programming with the help of the classic C Programming language book written by Brian Kernighan and Dennis Ritchie.
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
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.
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.
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.
ICML+
https://icml.cc/
NeurIPS+
https://neurips.cc/
相关职位
社招自动驾驶
1. 负责自动驾驶端到端模型的设计与研发; 2. 参与、负责关键算法的设计、实现、优化,如 静态感知、导航地图融合、轨迹预测等; 3. 参与、负责训练及验证数据集的构建,以数据驱动方式持续优化模型能力。
社招CSIG技术
1.负责开发和优化自动驾驶端到端算法及系统,整合感知、预测、建图、决策等各传统模块,并负责端到端算法模型的车端移植与模块部署; 2.设计、开发和优化自动驾驶端到端算法,分阶段实现感知端到端、感知预测端到端、感知决策端到端三阶段算法研究; 3.开发、维护车端基于ROS2通信的端到端自动驾驶工程链路,提升车端识别准召、FPS、资源开销等性能指标; 4.与团队合作,进行算法性能评估和优化,对接上下游模块,提供满足下游需求的算法输出。
更新于 2025-05-26
社招3年以上自动驾驶
1.负责自动标注算法研发,实现多模态数据的联合生成与标注,涉及算法有点云分割&检测/动静态BEV/OCC/VLM等,支撑端到端/VLA项目落地; 2.负责云端VLM/VLA算法研发,并落地车云端; 3.负责重建生成算法在自动驾驶场景的研发,应用于静态标注和数据合成业务中; 4.探索新的模型训练方式在自动驾驶场景的落地,包括自监督/弱监督/增量训练/强化学习/数据配比方案等。 5.跟踪最新的大模型和人工智能发展动态,持续迭代更新多模态大模型方案; 6.主导关键技术的专利撰写和论文发表工作。