小米深度学习算法工程师-实习
实习兼职地点：北京状态：招聘
任职要求
任职要求 基础技能： 1.自动化、车辆工程、机械、能动、计算机科学或相关专业本科及以上学历； 2.熟练掌握Python及常用库（Pandas、NumPy、Scikit-learn、PyTorch/TensorFlow）； 3.熟悉机器学习基础理论及经典时序预测模型（如ARIMA、RNN、LSTM、transformer等）。 项目经验（满足至少一项）： 1.曾参与时序预测相关项目，有实际建模经验（学术研究/比赛/企业项目均可）； 2.理解时序数据特性（季节性、趋势性、噪声处理等），熟悉差分、滑动窗口等预处理方法； 3.了解深度学习在时序领域的应用（如TCN、Transformer时序变体）。 加分项： 1.具有整车能耗分析、热管理能耗分析等相关知识； 2.有Kaggle/KDD Cup等时序相关比赛经验； 3.发表过时序预测相关论文或开源项目贡献。
工作职责
工作内容： 1.负责整车热管理与能耗预测算法研发、用机器学习算法对整车热管理与能耗进行预测 2.设计并开发时序预测模型； 3.参与完整的数据分析流程：数据清洗、特征工程、模型选型与调优、结果可视化及落地部署； 4.探索前沿时序算法； 5.与业务团队协作，推动模型在真实场景中的价值落地。
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.
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
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.
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.
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.
LSTM+
https://colah.github.io/posts/2015-08-Understanding-LSTMs/
Humans don’t start their thinking from scratch every second.
https://d2l.ai/chapter_recurrent-modern/lstm.html
The term “long short-term memory” comes from the following intuition.
https://developer.nvidia.com/discover/lstm
A Long short-term memory (LSTM) is a type of Recurrent Neural Network specially designed to prevent the neural network output for a given input from either decaying or exploding as it cycles through the feedback loops.
https://www.youtube.com/watch?v=YCzL96nL7j0
Basic recurrent neural networks are great, because they can handle different amounts of sequential data, but even relatively small sequences of data can make them difficult to train.
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.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
Kaggle+
[英文] Kaggle Learn
https://www.kaggle.com/learn
Gain the skills you need to do independent data science projects.
相关职位
实习
1. 汽车业务：协助算法工程师完成汽车能耗、运动控制相关的算法研究与开发工作，将行业内相关的前沿技术和最新研究成果应用到实际业务中 2. 大家电业务：协助算法工程师完成空调、冰箱、洗衣机相关的AI算法研究和开发工作，将行业内前沿智能控制算法和大模型技术应用到实际业务中 3. 参与能耗预测、温度预测等时序预测问题的解决，合理构建特征，选择模型，实现精准预测 4. 参与智能控制算法、大模型的研究与验证，协助优化算法模型 5. 协助算法工程师完成上述相关算法的端侧部署、测试，支持量产交付
更新于 2025-07-01
实习
1、负责图像、视频的多模态内容生成工作，应用Transformer、Stable Diffusion等技术赋能核心业务; 2、利用前沿深度学习算法，对图像、视频进行编码、压缩、重建或生成; 3、探索图像和视频的前沿技术，负责算法模型迭代升级。
更新于 2025-04-24
实习
1、面向小米广告业务需求开发算法解决方案，包括广告召回、点击率预估与大规模推荐算法等 2、从数据中发现现有系统和算法的不足，提出改进算法并推动实现； 3、研究推荐营销核心算法，使用海量用户行为数据对用户长短期兴趣建模，并且结合业务场景进行效果改进； 4、深度学习、迁移学习、多目标学习、强化学习等模型的设计、优化、应用和业界前沿算法研究； 5、追踪业界前沿算法优化技术，结合业务特点，对前沿的算法技术进行应用与创新。
更新于 2025-09-26