MiniMax大模型工程师-RL框架&RL推理
社招全职地点：北京 | 上海状态：招聘
工作描述
职位描述 RL 正在成为提升大模型能力的重要方向。大规模 RL 的效率和上限，不仅取决于算法设计，也高度依赖底层系统能力，包括 RL 框架、Rollout、推理 serving、调度策略、环境交互和系统稳定性。 MiniMax 自研强化学习训练系统 Forge，支撑大规模 RL 训练和 Rollout。Rollout 往往占据 RL 循环中的大量 wall-clock time，其生成效率、稳定性和灵活性，会直接影响算法迭代速度、实验规模和策略探索空间。 我们关注 RL 训练链路中的核心系统问题：如何更高效地生成轨迹，如何支持多轮交互、工具调用和复杂环境，如何降低长尾延迟，如何提升推理吞吐和资源利用率，以及如何让推理系统、模型结构和训练算法协同优化。 你会参与： 1. 建设和优化 Forge RL 框架，支撑大规模 RLHF / RLVR / Agentic RL 等训练任…
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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
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/
强化学习+
https://cloud.google.com/discover/what-is-reinforcement-learning?hl=en
Reinforcement learning (RL) is a type of machine learning where an "agent" learns optimal behavior through interaction with its environment.
https://huggingface.co/learn/deep-rl-course/unit0/introduction
This course will teach you about Deep Reinforcement Learning from beginner to expert. It’s completely free and open-source!
https://www.kaggle.com/learn/intro-to-game-ai-and-reinforcement-learning
Build your own video game bots, using classic and cutting-edge algorithms.
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.
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
系统设计+
https://roadmap.sh/system-design
Everything you need to know about designing large scale systems.
https://www.youtube.com/watch?v=F2FmTdLtb_4
This complete system design tutorial covers scalability, reliability, data handling, and high-level architecture with clear explanations, real-world examples, and practical strategies.
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实习算法
RL 正在成为提升大模型能力的重要方向。大规模 RL 的效率和上限，不仅取决于算法设计，也高度依赖底层系统能力，包括 RL 框架、Rollout、推理 serving、调度策略、环境交互和系统稳定性。
更新于 2026-09-08北京|上海
实习算法
RL 正在成为提升大模型能力的重要方向。大规模 RL 的效率和上限，不仅取决于算法设计，也高度依赖底层系统能力，包括 RL 框架、Rollout、推理 serving、调度策略、环境交互和系统稳定性。
更新于 2026-09-07北京|上海
校招算法
我们希望你在某个领域有真正的深度——推理加速、GPU 性能优化、分布式系统、RL 工程，都行——同时对算法前沿保持真实的好奇心。你不需要什么都懂，但你应该知道自己不懂的东西在哪，并且想去弄懂它。 1.
更新于 2026-09-07北京|上海
社招3-5年引擎
【任职资格】 1.熟练掌握Megatron/DeepSpeed/FSDP等框架的研发，熟练掌握模型并行分布式技术 2.对大语言模型算法感兴趣，有机器学习算法知识背景，因为我们日常也会训练模型来确保框架
更新于 2026-04-02北京|上海