小米高级算法工程师(工业视觉)
社招全职5年以上A34813地点:北京状态:招聘
工作描述
任职要求 1. 教育背景与经验 - 计算机、人工智能、自动化、数学、电子信息等相关专业,硕士及以上学历; - 5年以上AI算法研发经验,其中至少1-2年专注于大模型(LLM或VLM等)相关领域的研发。 2. 工程与编程能力: - 精通Python编程,熟练掌握PyTorch/TensorFlow/JAX等至少一种主流深度学习框架,能快速复现前沿算法; - 具备良好的软件工程素养和代码规范。 3. 算法能力: - 熟悉CLIP、SAM、QWEN系列等多模态模型的原理和应用,具备处理图像-文本对齐、视觉问答(VQA)、图像描述生成等任务的实践经验; - 精通Agent的设计理念和技术栈,有使用LangChain、LlamaIndex或自研框架构建基于知识库的智能Agent(如RAG系统)的完整项目经验; - 具备丰富的大模型微调(Fine-tuning)实战经验,熟练掌握LoRA、QLoRA等高效微调技术,强化学习算法PPO,GRPO,SAPO等,至少掌握trl,swift一种框架并有成功将模型应用于特定业务的落地案例; 4. 综合素质: - 具备出色的问题分析与解决能力…
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包括英文材料
学历+
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/
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
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.
PyTorch+
https://datawhalechina.github.io/thorough-pytorch/
PyTorch是利用深度学习进行数据科学研究的重要工具,在灵活性、可读性和性能上都具备相当的优势,近年来已成为学术界实现深度学习算法最常用的框架。
https://www.youtube.com/watch?v=V_xro1bcAuA
Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python.
TensorFlow+
https://www.youtube.com/watch?v=tpCFfeUEGs8
Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you’ve come to the right place.
https://www.youtube.com/watch?v=ZUKz4125WNI
This part continues right where part one left off so get that Google Colab window open and get ready to write plenty more TensorFlow code.
JAX+
https://docs.jax.dev/en/latest/notebooks/thinking_in_jax.html
JAX is a library for array-oriented numerical computation, with automatic differentiation and JIT compilation to enable high-performance machine learning research.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
AI agent+
https://www.ibm.com/think/ai-agents
Your one-stop resource for gaining in-depth knowledge and hands-on applications of AI agents.
LangChain+
https://python.langchain.com/docs/tutorials/
New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications.
https://www.freecodecamp.org/news/beginners-guide-to-langchain/
LangChain is a popular framework for creating LLM-powered apps.
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