小米高级算法工程师(问答RAG+Agent)
社招全职A22739A地点:北京状态:招聘
任职要求
1.硕士及以上学历,计算机科学、自然语言处理、机器学习相关专业。 2.熟练掌握大模型微调优化和算法原理,具备分布式训练、模型压缩、推理加速等实战经验。 3.深入理解Transformer、Prompt Tuning、RLHF、强化学习等技术原理,有百亿参数级大模型调优经验。 4.具备垂直领域问答、大模型RAG任务落地经验。 5.优先条件: 在ACL/EMNLP/NeurIPS等顶会发表过与大模型相关论文。 具备垂直领域问答系统等实际项目经验。 熟悉大模型生成评测基准。
工作职责
1.核心算法研发方面:负责大语言模型的核心算法研究与工程化落地,构建小米IoT商品理解、推理和生成能力的智能问答Agent系统。 2.RAG领域知识库体系构建:基于小米IoT生态链说明书知识,构建包括商品参数、功能问答、设置操作说明、故障排查等多源知识库。 3.RAG检索优化:优化改写、粗召、rerank等业务精排模型,提升大模型知识检索准确率。 4.探索IoT问答场景下的模型预训练、指令微调(Instruction Tuning)、对齐优化(Alignment)等关键技术,提升大模型在小米IoT商品问答中的表现。 5.技术前沿探索:跟踪大模型与Agent领域最新进展,推动小米产品领域问答场景下的技术创新与专利沉淀。
包括英文材料
学历+
NLP+
https://www.youtube.com/watch?v=fNxaJsNG3-s&list=PLQY2H8rRoyvzDbLUZkbudP-MFQZwNmU4S
Welcome to Zero to Hero for Natural Language Processing using TensorFlow!
https://www.youtube.com/watch?v=R-AG4-qZs1A&list=PLeo1K3hjS3uuvuAXhYjV2lMEShq2UYSwX
Natural Language Processing tutorial for beginners series in Python.
https://www.youtube.com/watch?v=rmVRLeJRkl4&list=PLoROMvodv4rMFqRtEuo6SGjY4XbRIVRd4
The foundations of the effective modern methods for deep learning applied to NLP.
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.
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/
Transformer+
https://huggingface.co/learn/llm-course/en/chapter1/4
Breaking down how Large Language Models work, visualizing how data flows through.
https://poloclub.github.io/transformer-explainer/
An interactive visualization tool showing you how transformer models work in large language models (LLM) like GPT.
https://www.youtube.com/watch?v=wjZofJX0v4M
Breaking down how Large Language Models work, visualizing how data flows through.
Prompt+
https://cloud.google.com/vertex-ai/generative-ai/docs/learn/prompts/introduction-prompt-design
A prompt is a natural language request submitted to a language model to receive a response back.
https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering
These techniques aren't recommended for reasoning models like gpt-5 and o-series models.
https://www.youtube.com/watch?v=LWiMwhDZ9as
Learn and master the fundamentals of Prompt Engineering and LLMs with this 5-HOUR Prompt Engineering Crash Course!
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.
RAG+
https://www.youtube.com/watch?v=sVcwVQRHIc8
Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer.
NeurIPS+
https://neurips.cc/
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