千问千问事业部-MOS 实验室-推荐/推送算法专家（大模型方向）-杭州/北京/广州
社招全职2年以上技术类-算法地点：北京 | 杭州 | 广州状态：招聘
工作描述
任职要求 1. 推荐领域资深背景： 拥有丰富的荐系统或推送业务经验，对召回、排序、重排等经典架构有深刻理解。 2. 大模型实战经验： 熟悉主流大模型的应用逻辑，有生成式推荐、Agent 推理或 LLM-based 策略优化实战经验者优先。 3. 策略与建模能力： ○ 精通传统推荐算法（如多任务学习、强化学习、序列建模）。 ○ 在推送算法、用户生命周期建模、或 Uplift Model 等增量建模方向有成功案例。 4. 敏锐的业务洞察： 能够从用户体验角度出发设计算法，对“主动服务”场景有独特的思考，不拘泥于单纯的技术实现。 5. 工程与硬技能： 极其扎实的编程功底（Python/Java/C++），熟悉主流深度学习框架，具备处理海量数据、实现复杂逻辑落地的能力。 加分项 ● 在推荐系统或 NLP 顶…
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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/
GBDT+
https://developers.google.com/machine-learning/decision-forests/intro-to-gbdt
Like bagging and boosting, gradient boosting is a methodology applied on top of another machine learning algorithm.
https://scikit-learn.org/stable/modules/ensemble.html
Ensemble methods combine the predictions of several base estimators built with a given learning algorithm in order to improve generalizability / robustness over a single estimator.
DeepFM+
https://d2l.ai/chapter_recommender-systems/deepfm.html
DeepFM consists of an FM component and a deep component which are integrated in a parallel structure.
https://deeprs-tutorial.github.io/WWW_DNN.pdf
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.
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.
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.
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.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
SQL+
https://liaoxuefeng.com/books/sql/introduction/index.html
什么是SQL？简单地说，SQL就是访问和处理关系数据库的计算机标准语言。
https://sqlbolt.com/
Learn SQL with simple, interactive exercises.
https://www.youtube.com/watch?v=p3qvj9hO_Bo
In this video we will cover everything you need to know about SQL in only 60 minutes.
Spark+
[英文] Learning Spark Book
https://pages.databricks.com/rs/094-YMS-629/images/LearningSpark2.0.pdf
This new edition has been updated to reflect Apache Spark’s evolution through Spark 2.x and Spark 3.0, including its expanded ecosystem of built-in and external data sources, machine learning, and streaming technologies with which Spark is tightly integrated.
推荐系统+
[英文] Recommender Systems
https://www.d2l.ai/chapter_recommender-systems/index.html
Recommender systems are widely employed in industry and are ubiquitous in our daily lives.
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