
MiniMax存储系统DevOps 工程师(大模型 / AI 基础设施方向)
社招全职5年以上基础架构地点:上海状态:招聘
工作描述
##职位描述 ###一句话定位 面向大模型训练、推理和数据清洗场景,负责存储系统与软硬件方案的选型、测试、交付、运维和性能优化,保障大规模 GPU / AI 集群稳定、高效运行。 ### 主要职责 1. 存储方案选型与交付 - 负责对象存储 S3、文件系统 NFS、高性能文件系统 PFS、KVCache 等存储系统的选型、测试、交付与运维。 - 制定存储产品技术路线,评估不同存储方案在 AI 场景下的适配性、稳定性和性价比。 - 推动 NVMe SSD、RDMA、分布式存储、新型文件系统等技术在大模型平台落地。 2. AI 场景存储性能测试 设计并实施面向真实 AI 负载的存储性能测试体系,覆盖: - 大模型训练: Checkpoint、Dataset 读取、训练过程中的伴生 I/O 负载; - 推理服务: 低延迟、高并发、小 I/O 访问; - 数据清洗与特征工程: 高吞吐、顺序 I/O、混合 I/O 访问。 输出性能评估与优化报告,为存储架构和产品选型提供依据。 3. 存储性能分析与优化 - 深入分析训练、推理链路中的 CPU、GPU、网络和存储协同…
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包括英文材料
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
S3+
https://aws.amazon.com/s3/getting-started/
You can use Amazon S3 to store and retrieve any amount of data at any time, from anywhere.
https://www.youtube.com/watch?v=tfU0JEZjcsg
Amazon S3 is the oldest and one of the most popular services on AWS.
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
特征工程+
https://www.ibm.com/think/topics/feature-engineering
Feature engineering preprocesses raw data into a machine-readable format. It optimizes ML model performance by transforming and selecting relevant features.
https://www.kaggle.com/learn/feature-engineering
Better features make better models. Discover how to get the most out of your data.
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
测试流程+
https://www.youtube.com/watch?v=3kzHmaeozDI
If you haven't come across unit testing and wondering what it's all about then take some time and watch this video.
https://www.youtube.com/watch?v=BQqzfHQkREo
https://www.youtube.com/watch?v=VywxIQ2ZXw4
This course will introduce you to Postman and is suited for beginners.
https://www.youtube.com/watch?v=zp5Jh2FIpF0
还有更多 •••
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