小米运筹优化算法工程师实习生
实习兼职地点：北京状态：招聘
任职要求
1. 运筹学、工业工程、自动化、计算机科学、数学、统计学、管理科学与工程等相关专业，硕士及以上学历； 2. 熟练掌握至少一门编程语言，如 Python（优先）、Java、C++ 等，熟练掌握常用数据结构和算法； 3. 具备扎实的运筹学基础，熟悉线性规划、整数规划、组合优化、网络流等核心概念和理论，熟悉启发式算法（如遗传算法、模拟退火、禁忌搜索等）； 4. 熟悉常用机器学习和深度学习算法，包括但不限于树模型、SVM、线性回归以及深度学习算法； 5. 有使用至少一种优化求解工具（如 Gurobi, Cplex, SCIP, OR-Tools）或数值计算库（如 NumPy, SciPy, Pandas）的课程项目或实验经验； 6. 优秀的沟通能力和表达能力，有创新精神，乐于接受挑战； 具有以下条件之一者优先： 1. 有排产排程、车辆路径规划、资源调度等相关项目经验者优先 2. 一周至少工作4天者优先
工作职责
1. 辅助完成AI在电动汽车智造领域的关键技术预研或项目落地； 2. 参与汽车工厂域算法项目预研，包括但不局限于预测、库存优化、排产排程、排班等项目，不断完善和优化算法，以技术驱动公司业务成长，体现技术价值；
包括英文材料
学历+
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.
Java+
https://www.youtube.com/watch?v=eIrMbAQSU34
Master Java – a must-have language for software development, Android apps, and more! ☕️ This beginner-friendly course takes you from basics to real coding skills.
C+++
https://www.learncpp.com/
LearnCpp.com is a free website devoted to teaching you how to program in modern C++.
https://www.youtube.com/watch?v=ZzaPdXTrSb8
数据结构+
https://www.youtube.com/watch?v=8hly31xKli0
In this course you will learn about algorithms and data structures, two of the fundamental topics in computer science.
https://www.youtube.com/watch?v=B31LgI4Y4DQ
Learn about data structures in this comprehensive course. We will be implementing these data structures in C or C++.
https://www.youtube.com/watch?v=CBYHwZcbD-s
Data Structures and Algorithms full course tutorial java
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/
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.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
Gurobi+
https://gurobi-machinelearning.readthedocs.io/en/stable/user/start.html
A Python package to help use trained regression models in mathematical optimization models.
https://www.youtube.com/watch?v=Er5RM06D9i8&list=PLHiHZENG6W8B_65-Unq-G59PtQtEc1Xj4
This session will provide a brief overview of the training.
CPLEX+
https://home.engineering.iastate.edu/~jdm/ee458/CPLEX-GettingStarted2017.pdf
Describes the components of CPLEX: Interactive Optimizer, Concert Technology, Callable Library.
https://www.ibm.com/docs/en/icos/22.1.2?topic=ide-getting-started-tutorial
A tutorial in which you launch the IDE, create an empty project, enter an OPL model, add data, add a settings file, create run configurations and execute them.
https://www.youtube.com/watch?v=70HH-GNR9uM
Introduction to CPLEX OPL, Work Environment, Creating a new project, run configuration, data and model files.
NumPy+
https://numpy.org/doc/stable/user/absolute_beginners.html
NumPy (Numerical Python) is an open source Python library that’s widely used in science and engineering.
[英文] NumPy - Learn
https://numpy.org/learn/
Below is a curated collection of educational resources, both for self-learning and teaching others, developed by NumPy contributors and vetted by the community.
https://www.kaggle.com/code/themlphdstudent/learn-numpy-numpy-50-exercises-and-solution
This kernel uses exercises of NumPy from the Machine Learning Plus webpage
https://www.youtube.com/watch?v=KHoEbRH46Zk
If you've heard of Pandas and NumPy, you may think one is simply a superset of the other.
https://www.youtube.com/watch?v=QUT1VHiLmmI
Learn the basics of the NumPy library in this tutorial for beginners.
https://www.youtube.com/watch?v=VXU4LSAQDSc
This video serves as an introduction to the NumPy Python library.
Pandas+
[英文] 10 minutes to pandas
https://pandas.pydata.org/docs/user_guide/10min.html
This is a short introduction to pandas, geared mainly for new users.
[英文] Cookbook - pandas
https://pandas.pydata.org/docs/user_guide/cookbook.html#cookbook
This is a repository for short and sweet examples and links for useful pandas recipes.
https://www.kaggle.com/learn/pandas
Solve short hands-on challenges to perfect your data manipulation skills.
https://www.youtube.com/watch?v=2uvysYbKdjM
I'm super excited for this one. We're doing another complete Python Pandas tutorial walkthrough.
https://www.youtube.com/watch?v=Mdq1WWSdUtw
Filtering, Joins, Indexing, Data Cleaning, Visualizations
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