小鹏汽车【27届校招】计算平台软件工程师
校招全职地点：上海 | 广州状态：招聘
任职要求
1、教育背景：计算机、软件工程、人工智能、数据科学等相关专业，本科及以上学历，硕博优先； 2、理论基础扎实： 精通分布式系统原理、并行计算、存储系统、数据库原理、数据湖/数据仓库理论、大规模机器学习等学科知识，有相关顶会/顶刊论文经历者优先； 3、技术能力突出： （1）熟练掌握至少一种主流分布式计算框架（如Spark、Flink、Ray等）和一种深度学习框架（如PyTorch、TensorFlow等）； （2）具备大数据存储与处理系统（如OSS、CPFS、Iceberg、Delta Lake、Hudi、StarRocks、ClickHouse、ElasticSearch、Milvus等）实操经验； （3）具备高性能数据检索、索引优化、海量数据管理等工程经验； 4、编程与工程能力强 （1）熟练掌握Python/Java/Scala/C++/Ru…
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工作职责
1、参与自动驾驶海量数据的采集、管理、处理与高效调度，设计与开发自动驾驶全链路数据平台，包括但不限于数据湖、数据仓库、分布式存储、流批一体计算与智能数据标注、数据治理等； 2、研发大规模分布式计算与训练平台，基于Spark、Flink、Ray、PyTorch等技术实现自动驾驶大模型的数据清洗、预处理、并行训练与推理，支持多GPU/多集群高性能任务编排与资源调度； 3、优化存储与检索架构，探索和实现包括OSS、CPFS、Iceberg、Delta Lake、Hudi、StarRocks、ClickHouse、ElasticSearch、Milvus等新一代高性能存储与检索方案，提升数据读写、索引、管理效率，赋能AI训练和推理； 4、参与团队架构设计与技术攻关，跟进学术前沿与业界动态，解决自动驾驶场景下数据一致性、扩展性、高可用、智能调度等核心难题； 5、推进工程实践落地与持续优化，深度参与端到端系统开发、自动化测试、上线发布与持续运维，推动数据与AI平台的稳定迭代和性能进化。
包括英文材料
数据科学+
https://roadmap.sh/ai-data-scientist
Step by step roadmap guide to becoming an AI and Data Scientist
学历+
分布式系统+
https://www.distributedsystemscourse.com/
The home page of a free online class in distributed systems.
https://www.youtube.com/watch?v=7VbL89mKK3M&list=PLOE1GTZ5ouRPbpTnrZ3Wqjamfwn_Q5Y9A
数据仓库+
https://www.youtube.com/watch?v=9GVqKuTVANE
From Zero to Data Warehouse Hero: A Full SQL Project Walkthrough and Real Industry Experience!
https://www.youtube.com/watch?v=k4tK2ttdSDg
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.
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.
Flink+
https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/learn-flink/overview/
This training presents an introduction to Apache Flink that includes just enough to get you started writing scalable streaming ETL, analytics, and event-driven applications, while leaving out a lot of (ultimately important) details.
https://www.youtube.com/watch?v=WajYe9iA2Uk&list=PLa7VYi0yPIH2GTo3vRtX8w9tgNTTyYSux
Today’s businesses are increasingly software-defined, and their business processes are being automated. Whether it’s orders and shipments, or downloads and clicks, business events can always be streamed. Flink can be used to manipulate, process, and react to these streaming events as they occur.
Ray+
https://github.com/ray-project/ray
Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
https://www.youtube.com/watch?v=FhXfEXUUQp0
In this video, I'll teach you everything you need to know about Apache Ray!
https://www.youtube.com/watch?v=fMiAyj2kgac
Using powerful machine learning algorithms is easy using Ray.io and Python.
https://www.youtube.com/watch?v=q_aTbb7XeL4
Parallel and Distributed computing sounds scary until you try this fantastic Python library.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
PyTorch+
https://datawhalechina.github.io/thorough-pytorch/
PyTorch是利用深度学习进行数据科学研究的重要工具，在灵活性、可读性和性能上都具备相当的优势，近年来已成为学术界实现深度学习算法最常用的框架。
https://www.youtube.com/watch?v=V_xro1bcAuA
Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python.
TensorFlow+
https://www.youtube.com/watch?v=tpCFfeUEGs8
Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you’ve come to the right place.
https://www.youtube.com/watch?v=ZUKz4125WNI
This part continues right where part one left off so get that Google Colab window open and get ready to write plenty more TensorFlow code.
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.
Iceberg+
https://iceberg.apache.org/spark-quickstart/
This guide will get you up and running with Apache Iceberg™ using Apache Spark™, including sample code to highlight some powerful features.
https://www.baeldung.com/apache-iceberg-intro
This tutorial will discuss Apache Iceberg, a popular open table format in today’s big data landscape.
https://www.youtube.com/watch?v=TsmhRZElPvM
You’ve probably heard about Apache Iceberg™—after all, it’s been getting a lot of buzz.
Delta Lake+
https://delta.io/learn/getting-started/
This guide helps you quickly explore the main features of Delta Lake.
[英文] Delta Lake Tutorials
https://delta.io/learn/tutorials/
Try out the latest tutorials for the open-source Delta Lake project.
[英文] Tutorial: Delta Lake
https://docs.databricks.com/aws/en/delta/tutorial
This tutorial introduces common Delta Lake operations on Databricks.
https://www.youtube.com/watch?v=fkWxiesfrgk
In this Delta Lake course, we will go though all the important concepts of Delta Lake.
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更新于 2026-07-03广州
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