
智能互联千问事业部-输入法算法工程师-北京
社招全职1年以上技术类-算法地点:北京状态:招聘
任职要求
- 计算机、数学、统计学或相关专业本科及以上学历。 - 具备扎实的编程功底,熟练掌握 Python / C++ 中的一种或多种,熟悉常见的数据结构与算法。 - 深入理解自然语言处理(NLP)基础理论,熟悉 RNN、LSTM、Transformer、BERT、GPT 等主流深度学习模型结构。 - 熟悉至少一种主流深度学习框架(如 PyTorch、TensorFlow、PaddlePaddle 等),并有实际的模型训练与调优经验。 - 对输入法或…
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工作职责
- 负责输入法核心算法的研发与优化,包括但不限于语言模型(LM)、解码搜索算法、拼写纠错、分词及词性标注等模块。 - 深入研究并落地大语言模型(LLM)在输入法场景的应用,如智能预测、上下文联想、文本润色及个性化生成等。 - 优化输入法的端侧模型,在保证预测准确率的同时,实现模型在移动设备上的轻量化部署与高效推理。 - 负责用户行为数据的挖掘与分析,通过用户画像和个性化算法,提升用户的打字效率与输入体验。 - 跟进学术界与工业界的前沿技术(如NLP、深度学习、推荐系统等),并推动其在输入法产品中的落地。
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.
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/
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.
RNN+
https://d2l.ai/chapter_recurrent-neural-networks/rnn.html
A neural network that uses recurrent computation for hidden states is called a recurrent neural network (RNN).
https://www.deeplearningbook.org/contents/rnn.html
Recurrent neural networks, or RNNs (Rumelhart et al., 1986a), are a family of neural networks for processing sequential data.
https://www.ibm.com/think/topics/recurrent-neural-networks
A recurrent neural network or RNN is a deep neural network trained on sequential or time series data to create a machine learning (ML) model that can make sequential predictions or conclusions based on sequential inputs.
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.
BERT+
https://www.youtube.com/watch?v=xI0HHN5XKDo
Understand the BERT Transformer in and out.
GPT+
https://www.youtube.com/watch?v=kCc8FmEb1nY
We build a Generatively Pretrained Transformer (GPT), following the paper "Attention is All You Need" and OpenAI's GPT-2 / GPT-3.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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