百度自动驾驶数据闭环高级后端工程师（J94282）
社招全职2年以上IDG地点：北京状态：招聘
任职要求
-2年及以上经验，本科及以上学历 -熟练的python语言技能，熟悉shell命令及开发，掌握python/c++/go其中一门语言，对多线程、异步、大数据、高并发等系统有独立设计经验，扎实的计算机科学基础，拥有缓存、消息队列，关系数据库，nosql，操作系统，网络协议等相关知识，并对其中任一项具备深入的理解和认识 -熟悉分布式计算相关技术，熟悉hadoop、spark、storm等系统原理和适用场景，并拥有集群设计和SRE经验，具备服务网格，大规模微服务集群及服务治理，监控系统相关工作经验 -掌握分布式存储系统，对elasticsearch、mongodb、hdfs的原理熟悉，并有PB级大规模高可用集群设计和运维经验。了解OLAP系统的特点 -学习能力强，有良好的逻辑思维能力、具备同质化问题的归纳和抽象能力，专注技术并追求最佳实践。强烈的责任心，并拥有良好的沟通与合作能力 -加分项：汽车技术相关背景，熟练的道路驾驶技能，汽车运动相关理论知识，机器学习/深度学习相关背景，机器人技术相关背景
工作职责
-负责自动驾驶数据全链路数据流构建，完成数据闭环下的AI Infra系统构建，包含挖掘相关框架、标注、数据管道、分布式训练、模型评测、推理和部署全链路的建设 -负责数据闭环系统稳定性和效率建设，对数据飞轮落地有想法和落地路径 -负责面向AI Infra 的数据存储系统建设，了解高吞吐下的Infra 框架设计 -负责面向大模型时代的工程架构优化工作，对各业务进行对接和合理化评估，针对现行系统中各种问题进行分析优化，给出设计优化方案并实现
包括英文材料
学历+
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.
Bash+
[英文] The Bash Guide
https://guide.bash.academy/
A quality-driven guide through the shell's many features.
https://www.youtube.com/watch?v=tK9Oc6AEnR4
Understanding how to use bash scripting will enhance your productivity by automating tasks, streamlining processes, and making your workflow more efficient.
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
Go+
https://www.youtube.com/watch?v=8uiZC0l4Ajw
学习Golang的完整教程！从开始到结束不到一个小时，包括如何在Go中构建API的完整演示。没有多余的内容，只有你需要知道的知识。
多线程+
https://liaoxuefeng.com/books/java/threading/basic/index.html
和单线程相比，多线程编程的特点在于：多线程经常需要读写共享数据，并且需要同步。
https://www.youtube.com/watch?v=_uQgGS_VIXM&list=PLsc-VaxfZl4do3Etp_xQ0aQBoC-x5BIgJ
https://www.youtube.com/watch?v=IEEhzQoKtQU
https://www.youtube.com/watch?v=mTGdtC9f4EU&list=PLL8woMHwr36EDxjUoCzboZjedsnhLP1j4
https://www.youtube.com/watch?v=TPVH_coGAQs&list=PLk6CEY9XxSIAeK-EAh3hB4fgNvYkYmghp
https://www.youtube.com/watch?v=xPqnoB2hjjA
This video is an introduction to multithreading in modern C++.
https://www.youtube.com/watch?v=YKBwKy5PrpQ
Rust threading is easy to implement and improves the efficiency of your applications on multi-core systems!
大数据+
https://www.youtube.com/watch?v=bAyrObl7TYE
https://www.youtube.com/watch?v=H4bf_uuMC-g
With all this talk of Big Data, we got Rebecca Tickle to explain just what makes data into Big Data.
高并发+
https://www.baeldung.com/concurrency-principles-patterns
In this tutorial, we’ll discuss some of the design principles and patterns that have been established over time to build highly concurrent applications.
https://www.baeldung.com/java-concurrency
Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.
https://www.oreilly.com/library/view/concurrency-in-go/9781491941294/
You’ll understand how Go chooses to model concurrency, what issues arise from this model, and how you can compose primitives within this model to solve problems.
https://www.oreilly.com/library/view/modern-concurrency-in/9781098165406/
With this book, you'll explore the transformative world of Java 21's key feature: virtual threads.
https://www.youtube.com/watch?v=qyM8Pi1KiiM
https://www.youtube.com/watch?v=wEsPL50Uiyo
缓存+
https://hackernoon.com/the-system-design-cheat-sheet-cache
The cache is a layer that stores a subset of data, typically the most frequently accessed or essential information, in a location quicker to access than its primary storage location.
https://www.youtube.com/watch?v=bP4BeUjNkXc
Caching strategies, Distributed Caching, Eviction Policies, Write-Through Cache and Least Recently Used (LRU) cache are all important terms when it comes to designing an efficient system with a caching layer.
https://www.youtube.com/watch?v=dGAgxozNWFE
消息队列+
https://www.youtube.com/watch?v=xErwDaOc-Gs
NoSQL+
https://nosql-database.org/
Everything about NoSQL Systems – Types, Benefits, and Real-World Uses
https://piaosanlang.gitbooks.io/mongodb/content/section1.1.html
NoSQL(NoSQL = Not Only SQL )，即"不仅仅是SQL"，指的是非关系型的数据库。是对不同于传统的关系型数据库管理系统的统称。
https://www.youtube.com/watch?v=0buKQHokLK8
NoSQL databases can operate in multiple modes: as key-value store, document store or wide column store.
Hadoop+
https://www.runoob.com/w3cnote/hadoop-tutorial.html
Hadoop 为庞大的计算机集群提供可靠的、可伸缩的应用层计算和存储支持，它允许使用简单的编程模型跨计算机群集分布式处理大型数据集，并且支持在单台计算机到几千台计算机之间进行扩展。
[英文] Hadoop Tutorial
https://www.tutorialspoint.com/hadoop/index.htm
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models.
Spark+
[英文] Learning Spark Book
https://pages.databricks.com/rs/094-YMS-629/images/LearningSpark2.0.pdf
This new edition has been updated to reflect Apache Spark’s evolution through Spark 2.x and Spark 3.0, including its expanded ecosystem of built-in and external data sources, machine learning, and streaming technologies with which Spark is tightly integrated.
Apache Storm+
[英文] Tutorial
https://storm.apache.org/releases/2.6.0/Tutorial.html
In this tutorial, you'll learn how to create Storm topologies and deploy them to a Storm cluster.
https://www.baeldung.com/apache-storm
This tutorial will be an introduction to Apache Storm, a distributed real-time computation system.
Service Mesh+
https://aws.amazon.com/cn/what-is/service-mesh/
服务网格是一个软件层，用于处理应用程序中服务之间的所有通信。该层由容器化微服务组成。随着应用程序的扩展和微服务数量的增加，监控服务的性能变得越来越困难。
https://aws.amazon.com/what-is/service-mesh/
A service mesh is a software layer that handles all communication between services in applications. This layer is composed of containerized microservices.
https://www.redhat.com/zh-cn/topics/microservices/what-is-a-service-mesh
服务网格是软件应用内的一个专用基础架构层，用于处理服务之间的通信。服务网格可以处理流量路由、安全防护、可观测性和弹性功能，同时对各个服务进行抽象化处理来降低复杂性。
微服务+
https://learn.microsoft.com/en-us/training/modules/dotnet-microservices/
Microservice applications are composed of small, independently versioned, and scalable customer-focused services that communicate with each other by using standard protocols and well-defined interfaces.
https://microservices.io/
Microservices - also known as the microservice architecture - is an architectural style that structures an application as a collection of two or more services.
https://spring.io/microservices
Building small, self-contained, ready to run applications can bring great flexibility and added resilience to your code.
https://www.ibm.com/think/topics/microservices
Microservices, or microservices architecture, is a cloud-native architectural approach in which a single application is composed of many loosely coupled and independently deployable smaller components or services.
https://www.youtube.com/watch?v=CqCDOosvZIk
https://www.youtube.com/watch?v=hmkF77F9TLw
Learn about software system design and microservices.
服务治理+
https://cloudnativecn.com/blog/istio-traffic-management-series-service-management-concept-theory/
通过阅读本文读者可以初步理解 Istio 流量治理的概念和相关知识框架。
https://juejin.cn/post/6844904006033080334
服务治理主要包括服务发现、负载均衡、限流、熔断、超时、重试、服务追踪等。我们今天要讲的，就是服务发现的内容。
ElasticSearch+
https://www.youtube.com/watch?v=a4HBKEda_F8
Learn about Elasticsearch with this comprehensive course designed for beginners, featuring both theoretical concepts and hands-on applications using Python (though applicable to any programming language). The course is structured in two parts: first covering essential Elasticsearch fundamentals including index management, document storage, text analysis, pipeline creation, search functionality, and advanced features like semantic search and embeddings; followed by a practical section where you'll build a real-world website using Elasticsearch as a search engine, working with the Astronomy Picture of the Day (APOD) dataset to implement features such as data cleaning pipelines, tokenization, pagination, and aggregations.
MongoDB+
https://learnxinyminutes.com/mongodb/
MongoDB is a NoSQL document database for high volume data storage.
https://studio3t.com/academy/#courses
The fastest way to learn MongoDB
https://www.youtube.com/watch?v=c2M-rlkkT5o
This video will give you and introduction to MongoDB in 1 Hour. Afterwards I recommend exploring aggregation, replication, and sharding.
https://www.youtube.com/watch?v=ExcRbA7fy_A&list=PL4cUxeGkcC9h77dJ-QJlwGlZlTd4ecZOA
You'll learn how to use MongoDB (a NoSQL database) from scratch. You'll also learn how to integrate it into a simple Node.js API.
HDFS+
https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html
The Hadoop Distributed File System (HDFS) is a distributed file system designed to run on commodity hardware.
https://www.ibm.com/cn-zh/think/topics/hdfs
Hadoop 分布式文件系统 (HDFS) 是一种管理大型数据集的文件系统，可在商用硬件上运行。
高可用+
https://redis.io/blog/high-availability-architecture/
A high available architecture is when there are a number of different components, modules, or services that work together to maintain optimal performance, irrespective of peak-time loads.
https://www.ibm.com/think/topics/high-availability
High availability (HA) is a term that refers to a system’s ability to be accessible and reliable close to 100% of the time.
OLAP+
https://www.youtube.com/watch?v=iw-5kFzIdgY
OLAP (for online analytical processing) is software for performing multidimensional analysis at high speeds on large volumes of data from a data warehouse, data mart, or some other unified, centralized data store.
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.
相关职位
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。
社招3年以上
工作地点：上海、广州、北京 团队目标： 我们致力于构建世界一流的自动驾驶数据闭环体系。您将成为团队中的“数据科学家”与“价值度量官”，通过深度洞察和数据驱动，量化数据闭环各环节的效能与质量，确保我们交付的每一份数据都能高效、精准地驱动算法进化，成为公司核心竞争力的基石。 1、数据闭环效能度量体系设计： 构建并持续优化数据从“采集需求提出”到“算法消费”的全链路核心指标体系。 设计科学、可量化的指标，如：端到端交付周期、数据质量有效率、场景覆盖度、数据利用率、算法迭代收益关联度等。 深入业务，理解算法迭代流程，建立数据服务对算法效能提升的价值归因模型。 2、深度洞察与根因分析： 基于指标体系，主动发现数据闭环中的效率瓶颈、质量洼地与资源浪费。 运用统计学方法和数据分析工具，进行深度根因分析。例如：交付延迟是源于采集困难、标注堆积，还是需求变更？质量下降是特定场景、特定供应商还是标注标准模糊导致？ 对数据的真实性和有效性具有敏锐的洞察力，能识别并排查数据异常、逻辑错误及潜在的“数据造假”行为。 3、数据产品与看板驱动决策： 主导开发和维护直观、实时的数据驾驶舱与可视化看板，为TPM、运营、执行及管理层提供决策支持。 将分析结论产品化，推动建立自动化监控预警机制（如：交付周期超时预警、质量波动预警）。 4、驱动业务优化： 与数据策略、运营、执行团队紧密协作，将数据分析结论转化为具体的流程优化建议、资源调配方案和质量改进措施。 通过数据反馈，驱动采集策略、标注标准、工具链的持续迭代。
更新于 2025-10-10
社招
自动驾驶视觉算法高级/资深工程师（占据网络） 1、车载视觉感知算法以及端到端算法方向，用于车端高阶辅助驾驶功能。 2、侧重视觉BEVNet以及Lidar感知，包含但不限于检测、分割、深度估计等任务。 3、负责障碍物感知模型车端交付。 4、负责障碍物感知用户车数据闭环，大模型数据挖掘，视觉3D重建Autolabel。 5、负责自驾感知Foundation Model，World Model E2E仿真和数据生成。
更新于 2023-08-30
社招3年以上自动驾驶
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。