
MiniMaxAI Data 研发工程师(大模型数据方向)
社招全职研发地点:上海 | 北京状态:招聘
工作描述
MiniMax 致力于构建下一代通用人工智能模型,覆盖文本、图像、视频、语音等多模态大模型方向。数据是大模型能力演进的核心基础,我们正在建设面向大模型时代的新一代 AI Data Infra 平台,支撑预训练、后训练、评测及模型迭代全过程的数据生产、管理与优化。我们希望寻找优秀的数据基础设施工程师,共同打造服务于全模态大模型的数据平台和 Pipeline 基础设施。 你将参与: 1. 建设面向大模型的数据基础设施,负责构建支撑海量 AI 数据的数据基础设施,包括: - 面向文本、图像、视频、语音等多模态数据的统一管理体系; - 支撑 PB 级数据的存储、计算、索引与分发能力; - 建设面向 AI 数据的数据湖/湖仓体系,支持数据版本管理、元数据管理和生命周期管理; - 优化数据访问链路,保障大规模模型训练任务的数据吞吐和稳定性。 2. 构建大模型训练与后训练数据 Pipeline,参与建设覆盖模型全生命周期的数据生产体系,包括: - 预训练数据 Pipeline:数据解析、清洗、过滤、去重、质量评估、分类采样; - 后训练数据 Pipeline:SFT、Preference Data、RLHF/RLAIF 数据构造及自动化评估; - 多模态数据处理:图像/视频/语音数据处理、Caption 生成、Embedding 提取和特征构建; - 数据合成、增强…
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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
SFT+
https://cameronrwolfe.substack.com/p/understanding-and-using-supervised
Understanding how SFT works from the idea to a working implementation...
RLHF+
[英文] What is RLHF?
https://aws.amazon.com/what-is/reinforcement-learning-from-human-feedback/
Reinforcement learning from human feedback (RLHF) is a machine learning (ML) technique that uses human feedback to optimize ML models to self-learn more efficiently.
https://www.ibm.com/think/topics/rlhf
Reinforcement learning from human feedback (RLHF) is a machine learning technique in which a “reward model” is trained with direct human feedback, then used to optimize the performance of an artificial intelligence agent through reinforcement learning.
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.
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/
SDK+
https://www.ibm.com/think/topics/api-vs-sdk
Learn about software development kits (SDKs) and application programming interfaces (APIs) and how they improve both software development cycles and the end-user experience (UX).
https://www.redhat.com/zh-cn/topics/cloud-native-apps/what-is-SDK
软件开发套件(SDK)是通常由硬件平台、操作系统(OS)或编程语言的制造商提供的一套工具。
开发框架+
[英文] Understanding Modern Development Frameworks: A Guide for Developers and Technical Decision-makers
https://www.freecodecamp.org/news/understanding-modern-development-frameworks-guide-for-devs/
数据治理+
https://www.ibm.com/think/topics/data-governance
Data governance is the data management discipline that focuses on the quality, security and availability of an organization’s data.
https://www.youtube.com/watch?v=uPsUjKLHLAg
Building data fabric eliminates the technological complexities of data governance so users can connect to the right data at the right time, regardless of where it resides.
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
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