快手大模型预训练/后训练算法专家
社招全职3-5年D12518地点:北京状态:招聘
任职要求
1、自然语言处理/机器学习/模式识别/人工智能/计算机等相关专业硕士及以上学历; 2、在NLP、LLM、深度学习、强化学习方面有一定研究基础,熟悉主流大模型和算法,并有丰富的实践经验; 3、较强的工程实现能力,熟练掌握 pytorch,熟悉DeepSpeed、Megatron、NeMo等分布式训练框; 4、有高质量论文发表者优先(如ACL、EM…
登录查看完整任职要求
微信扫码,1秒登录
工作职责
1、预训练模型结构和训练任务优化,提升预训练模型学习世界知识的能力; 2、持续收集和清洗大规模预训练数据,并研究数据构成和学习顺序对大模型效果的影响; 3、参与预训练模型评测,包括评测流程建设和完善、评测方法设计和优化等; 4、参与大模型Alignment相关工作,包括: a.Alignment方法设计与研究,包括SFT和 RLHF等相关的算法研究; b.Alignment整体数据建设,包括数据构建、标注以及分析其对模型能力的影响; c.从下游调优的角度探索如何提升大模型的逻辑推理能力。
包括英文材料
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.
模式识别+
https://www.mathworks.com/discovery/pattern-recognition.html
Pattern recognition is the process of classifying input data into objects, classes, or categories using computer algorithms based on key features or regularities.
https://www.microsoft.com/en-us/research/wp-content/uploads/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf
Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science.
学历+
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
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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.
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.
还有更多 •••
相关职位
社招5年以上混元-模型算法技
1.负责生成式大模型预训练相关的工作,包括但不限于:大规模模型预训练,长文本预训练,线性模型结构探索; 2.探索与跟进前沿技术,寻求技术突破,推动机器在AIGC能力的提升和突破; 3.探索高效的模型知识嵌入方法以及模型知识在线学习更新; 4.探索文本模型预训练的scaling law,在小规模小成本下更精准地预测大规模训练后的表现。
更新于 2025-12-31北京

社招技术类
1、深入理解电商平台业务场景,负责自然语言处理(NLP)、语义分析、人机对话模型等核心算法的研究与实现; 2、基于电商业务场景数据,重点负责大模型后训练算法,以及策略优化等相关工作; 3、负责搭建和优化Agentic系统,挑战将前沿Agent架构和算法应用于大规模电商核心业务,打开业务增长空间。 4、跟踪行业前沿技术,探索Agentic RL、DeepSearch、高效大模型等技术,参与新一代基座模型的调优与创新。
更新于 2026-01-08上海|北京
社招3年以上技术类-算法
负责蚂蚁集团语言大模型的评测算法研究与应用,搭建业界领先的大模型评测体系,精准全面地评估大模型的能力。基于AIGC等技术建设高质量评测数据集,与业界公开评测集有机结合,深入大模型预训练、后训练、深度思考等各个阶段,利用大模型等技术提高评测效率和准确性,通过高效高质量评测提升语言大模型、垂域大模型的能力和用户体验。
更新于 2026-01-14北京|杭州