理想汽车基座模型-大模型算法工程师-智能体算法-北京
校招全职算法地点：北京状态：招聘
包括英文材料
学历+
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.
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.
SFT+
https://cameronrwolfe.substack.com/p/understanding-and-using-supervised
Understanding how SFT works from the idea to a working implementation...
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.
RAG+
https://www.youtube.com/watch?v=sVcwVQRHIc8
Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer.
NeurIPS+
https://neurips.cc/
相关职位
校招算法
1.负责VLA基座大模型的架构设计与优化，包括但不限于MoE、MoD、稀疏注意力机制、快慢双系统以及多模态架构设计等 2. 负责VLA训练范式探索，包括但不限于预训练、RL等 3. 负责VLA基座大模型的Scaling Law建设 4. 负责MindVLA后训练算法研究和落地，研究面向L3 Agent的后训练范式，包括监督微调、通用强化学习、智能体强化学习等技术； 5. 参与下一代VLA基座模型的探索与创新研究，打造技术影响力。
社招3年以上智能与信息技术
1. 负责语言大模型基座在汽车设计、生产、制造、售后、运营全生命周期场景语料的训练，包括训练语料优化与合成、基座模型架构、百亿~千亿基座训练、各项基座能力优化等； 2. 负责研发知识增强大语言模型技术，包括大模型领域适配、知识对齐、知识增强等，在车企场景构建专业知识驱动的智能体应用； 3. 跟踪和研究前沿的大模型、智能体（Agent）等技术方向，推动相关领域技术创新。
社招ACG
-围绕大模型打造次世代的智能对话能力，例如实体抽取，意图识别、上下文记忆，多对话引擎切换 -建设文档问答、表格问答、FAQ等基于知识的对话能力，如 NL2SQL、Agentic-RAG -建设新一代数字员工产品，熟悉智能体基座模型领域，有机会研发遵循SOP执行的营销对话智能体 -梳理业务场景的会话，整理成训练大模型需要的训练数据，优化大模型专项能力（数值计算、日期比较、任务规划、工具选择等） -探索高性能，低成本的对话实现，最大化客户价值
更新于 2025-07-11