京东大模型算法研究员
社招全职算法开发岗地点:北京状态:招聘♡ 收藏
工作描述
任职要求 1.扎实的机器学习、NLP、RL基础和出色的创新能力,在ACL/EMNLP/NAACL/NeurIPS/ICML/ICLR等顶级会议上发表论文者优先; 2.在预训练、后训练、强化学习方向有深刻研究; 3.优秀的代码能力、数据结构和基础算法功底,熟练C/C++或Python,ACM/ICPC、NOI/IOI、Top Coder、Kaggle等…
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包括英文材料
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.
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.
ACL+
https://www.aclweb.org/portal/
Computational linguistics is the scientific study of language from a computational perspective.
EMNLP+
NeurIPS+
https://neurips.cc/
ICML+
https://icml.cc/
ICLR+
https://iclr.cc/
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.
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实习Data Inn
岗位职责: - 参与大模型预训练、后训练、强化学习、推理或 Agent 等方向的研究。 - 阅读和复现有价值的论文,在现有方案上提出并验证自己的改进。 - 参与训练数据的构建、清洗、筛选和质量分析。
更新于 2026-08-25深圳