阿里云阿里云智能-多模数据湖计算引擎与数据算法专家-杭州/北京
社招全职3年以上地点:北京 | 杭州状态:招聘♡ 收藏
工作描述
任职要求 职位要求 1、计算机、人工智能等相关专业本科及以上学历,3 年以上相关经验;精通 Python / C++ 等语言。 2、在以下方向中至少一个有深入积累,并对另一方向有了解: 算法方向:在图像识别、视频处理、特征提取、自动标注等多模态数据处理算法方向有深入实践,能独立完成算法设计、实现与效果评估; 引擎方向:熟悉 Ray、Daft、Spark、Flink 中至少一种,有分布式数据处理、向量化执行、算子融合或模型推理工程化经验。 3、熟悉 CPU/GPU 异构计算,有大规模数据处理系统的核心模块研发或数据产线规模化落地经验。 4、具备良好的需求理解与协作能力,重视工程质量与交付效果。 加分项 1、熟悉数据湖技术栈,包括对象存储、Iceberg、Parquet、Lance 等格式、元数据管理与 ACID 事务…
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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.
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
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/
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.
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.
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.
Parquet+
https://www.youtube.com/watch?v=KLFadWdomyI
Learn all about Apache Parquet, a column-based file format that's popular in the Hadoop/Spark ecosystem.
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