小鹏汽车【26届校招】VLM/VLA 大模型算法工程师
校招全职地点:深圳状态:招聘
任职要求
任职要求: - 计算机、人工智能、自动化等相关专业硕士及以上学历; - 具备扎实的深度学习基础,熟悉 Transformer、BERT、ViT、CLIP、BLIP 等主流视觉-语言模型架构; - 有大模型(VLM、LLM)训练/推理优化经验,熟悉其在多模态任务中的应用; - 有 VLA 建模、生成式模型(如diffusion)、多模态强化学习相关项目背景; - 熟练使用 PyTorch、TensorFlow 等深度学习框架,具备良好的工程能力和代码实现能力; - 良好的团队协作与沟通能力,具备快速学习和解决问题的能力。 加分项: - 熟悉机器人感知与控制领域,理解人形机器人操作、导航、交互、动作轨迹预测等基本任务流程; - 有参与实际机器人系统或多模态交互系统开发的项目经验; - 熟悉开源大模型生态(如 LLaVA, Pi0, RT-2, OpenVLA 等)并有实际使用或改进经验; - 具备从零构建多模态系统或算法平台的能力。
工作职责
- 负责多模态大模型(VLM: Vision-Language Model / VLA: Vision-Language-Action Model)在人形机器人中的算法设计与开发,将VLM/VLA 应用于人形机器人的智能操作与人机交互任务; - 参与大模型的预训练、后训练(SFT + RL)及部署工作,支持机器人在复杂环境下的感知与行为能力; - 与机器人平台团队、硬件团队紧密协作,实现模型在实际机器人系统中的高效运行; - 跟踪前沿研究,推动新技术在产品中的落地应用。
包括英文材料
学历+
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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.
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
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.
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.
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.
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/
相关职位
校招
1.研发业界一流物理AI系统,包括不限于模仿学习, 强化学习, vla, vlm等训练系统与算法架构; 2.参与自动驾驶系统中机器学习算法的研究、开发与优化,包括但不限于深度学习算法在端到端感知大模型、规控大模型、视觉语言大模型等方面的应用; 3.设计和实现机器学习模型的训练流程,包括选择合适的优化算法、调整超参数、评估模型性能等,确保模型在不同场景下的稳定性和可靠性。
更新于 2025-07-01
校招
- 探索通用算法并应用于工业机器人场景任务,具备物体泛化、任务泛化、场景泛化能力 - 多模态大模型VLA/VLM在工业类机器人中的算法设计、智能控制和人机交互前瞻技术研究 - 多机器人协同作业与调度,控制机器人与物理世界交互 - 基于创新实验室,构建多台工业/协作机器人/人形机器人协同工作环境
更新于 2025-08-14