小米视觉多模态算法工程师
社招全职4年以上A113887地点:北京状态:招聘
任职要求
1、本科及以上学历,视觉、自然语言处理、机器学习、人工智能相关专业。 2、4年以上的大模型、强化学习或深度学习项目经历,对相关算法有深入理解。 3、对大模型技术有深刻了解,具备较强的探索、实践动手能力,有语音或者视觉多模态背景优先。 4、熟练使用一种或几种深度学习框架(如pytorch、tensorflow、paddlepaddle等)。 5、具有良好的分析问题和解决问题的能力,有顶级会议或者刊物发表论文者优先。
工作职责
1、负责多模态大模型在图像理解方向的算法研发工作。 2、结合产品需求,负责算法的设计、开发、验证、集成、优化和维护,解决算法产品化过程中的各种技术问题,确保算法达到上线要求。 3、跟进相关领域前沿进展,并结合产品对算法进行优化,使相关产品效果达到业界领先水平。
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
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.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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/
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.
PaddlePaddle+
https://learnopencv.com/paddlepaddle/
PaddlePaddle (PArallel Distributed Deep LEarning) is an open-source deep learning framework released by Baidu in 2016.
https://www.paddlepaddle.org.cn/tutorials
本课程采用飞桨特色的「横纵式」 教学法,从易到难,学习难度逐层递进,并结合图形和案例进行讲解,力求让刚接触深度学习的读者可以快速理解。
相关职位
社招5-10年
1、针对物流领域场景进行深入的视觉算法研发,包括但不限于图像生成、图像理解、视频生成、视频理解等; 2、负责垂域多模态大模型的继续预训练、SFT等工作,积极跟进AIGC业内应用趋势,包括但不限于MoE、Agent、O1等方向。
更新于 2025-06-10
实习
1. 深入调研多模态大模型、计算机视觉、大模型推理以及强化学习等方向的前沿技术,并结合产品对算法进行优化,使相关产品效果达到业界领先水平; 2. 将多模态大模型落地到小米各个产品,结合产品需求,参与算法的设计、开发、验证、集成、优化和维护,解决算法产品化过程中的各种技术问题,确保达到上线要求; 3. 参与相关领域学术研究,产出具有业界行业影响力的科研成果;
更新于 2025-08-04
实习
1. 深入调研多模态大模型、计算机视觉、大模型推理以及强化学习等方向的前沿技术,并结合产品对算法进行优化,使相关产品效果达到业界领先水平; 2. 将多模态大模型落地到小米各个产品,结合产品需求,参与算法的设计、开发、验证、集成、优化和维护,解决算法产品化过程中的各种技术问题,确保达到上线要求; 3. 参与相关领域学术研究,产出具有业界行业影响力的科研成果;
更新于 2025-09-10