蚂蚁金服蚂蚁集团-3D建模技术专家-杭州
社招全职3年以上技术-开发地点：杭州状态：招聘
任职要求
● 3年以上3D建模/计算机视觉算法研发经验。 ● 扎实的3D数学基础（线性代数、计算几何、多视图几何）。 ● 熟练掌握点云处理（PCL/Open3D/LiDAR点云滤波），Mesh建模（泊松重建/拓扑优化/非流形修。复），Learning-based MVS（MVSNet/PatchMatchNet等）。 ● 编程能力： 熟练使用Python/C++，熟悉PyTorch/TensorFlow。 ● 发表过CVPR/ICCV/SIGGRAPH等相关论文优先（三维重建、计算机视觉方向）。 ● 有大规模3D重建项目经验优先（数字城市、自动驾驶高精地图等）。 ● 熟悉GPU计算优化（CUDA/OpenCL/TensorRT）的优先。 ● 了解DCC工具开发（Maya/Blender插件）或游戏引擎优化的优先。
工作职责
● 负责3D数据重建，研发基于深度学习的多视图立体重建（Learning-based MVS），提高深度估计、点云配准及表面重建质量。 ● 优化三维扫描点云处理（滤波、配准、特征提取），提高建模自动化程度；探索神经渲染（NeRF/Gaussian Splatting）与传统三维建模的结合。 ● 负责高质量Mesh建模，实现工业级精度Mesh重建（泊松重建、隐式场优化、拓扑修复）。 ● 优化3D建模算法性能，提升GPU/移动端运算效率。 ● 结合DCC工具（Blender/Maya）或游戏引擎（UE/Unity），推动3D资产自动化生产。
包括英文材料
OpenCV+
https://learnopencv.com/getting-started-with-opencv/
At LearnOpenCV we are on a mission to educate the global workforce in computer vision and AI.
https://opencv.org/university/free-opencv-course/
This free OpenCV course will teach you how to manipulate images and videos, and detect objects and faces, among other exciting topics in just about 3 hours.
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/
Open3D+
[英文] Introduction
https://www.open3d.org/docs/release/introduction.html
Open3D: A Modern Library for 3D Data Processing
https://www.youtube.com/watch?v=zF3MreN1w6c
Inside my school and program, I teach you my system to become an AI engineer or freelancer.
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
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.
CVPR+
https://cvpr.thecvf.com/
ICCV+
https://iccv.thecvf.com/
ICCV is the premier international computer vision event comprising the main conference and several co-located workshops and tutorials.
自动驾驶+
https://www.youtube.com/watch?v=_q4WUxgwDeg&list=PL05umP7R6ij321zzKXK6XCQXAaaYjQbzr
Lecture: Self-Driving Cars (Prof. Andreas Geiger, University of Tübingen)
https://www.youtube.com/watch?v=NkI9ia2cLhc&list=PLB0Tybl0UNfYoJE7ZwsBQoDIG4YN9ptyY
You will learn to make a self-driving car simulation by implementing every component one by one. I will teach you how to implement the car driving mechanics, how to define the environment, how to simulate some sensors, how to detect collisions and how to make the car control itself using a neural network.
CUDA+
https://developer.nvidia.com/blog/even-easier-introduction-cuda/
This post is a super simple introduction to CUDA, the popular parallel computing platform and programming model from NVIDIA.
https://www.youtube.com/watch?v=86FAWCzIe_4
Lean how to program with Nvidia CUDA and leverage GPUs for high-performance computing and deep learning.
OpenCL+
https://developer.nvidia.com/opencl
OpenCL™ (Open Computing Language) is a low-level API for heterogeneous computing that runs on CUDA-powered GPUs.
https://engineering.purdue.edu/~smidkiff/ece563/NVidiaGPUTeachingToolkit/Mod20OpenCL/3rd-Edition-AppendixA-intro-to-OpenCL.pdf
we will give a brief overview of OpenCL for CUDA programers.
[英文] Hands On OpenCL
https://handsonopencl.github.io/
An open source two-day lecture course for teaching and learning OpenCL
https://leonardoaraujosantos.gitbook.io/opencl/chapter1
Open Computing Language is a framework for writing programs that execute across heterogeneous platforms.
https://ulhpc-tutorials.readthedocs.io/en/latest/gpu/opencl/
OpenCL came as a standard for heterogeneous programming that enables a code to run in different platforms.
https://www.youtube.com/watch?v=4q9fPOI-x80
This presentation will show how to make use of the GPU from Java using OpenCL.
TensorRT+
https://docs.nvidia.com/deeplearning/tensorrt/latest/getting-started/quick-start-guide.html
This TensorRT Quick Start Guide is a starting point for developers who want to try out the TensorRT SDK; specifically, it demonstrates how to quickly construct an application to run inference on a TensorRT engine.
相关职位
社招3年以上研发类
1. 负责3D建模算法研究与应用，包括但不限于Gaussian Splatting建模，位姿估计，光照估计、可微渲染。 2. 研究AIGC算法在移动终端和3D建模算法中的算法研发，推动可控生成，画质增强，新视点生成等核心技术的探索。 3. 与工程、产品团队配合，推动团队成果的应用落地； 4. 带领实习生发表前沿学术论文，撰写专利等，推进技术进步。
社招
设计并实现高效的2D/3D人脸/人体生成、重建与编辑算法，包括但不限于：几何建模、纹理合成、表情与姿态生成。 研发高保真数字人驱动技术，如：基于语音/文本的表情/口型/动作同步生成 (Audio/Text-to-Face/Body Animation)，基于视频的动作捕捉与迁移。 探索并应用生成式模型 (如 GANs, Diffusion Models, VAEs, NeRF 等) 于数字人的创建、编辑、动画和渲染环节。
社招5年以上技术类
1、负责视觉检测识别类项目解决方案原型设计与落地； 2、业务需求收集、整理、分析与反馈，已有方案拓展优化和新方案可行性验证； 3、主导相关设备选型和供应商筛选、产品验收工作； 4、和软件/算法等团队一起，完成样机开发，调试等，解决关键技术问题，并不断优化改进。
更新于 2023-12-26
社招5年以上技术-开发
● 负责3D建模、渲染引擎的架构设计、研发及性能优化，支持高精度实时/离线渲染需求。 ● 主导3D图形算法开发，包括光照计算（PBR）、材质系统、LOD（细节层次）优化、物理模拟（碰撞、流体等）。 ● 优化渲染管线（Deferred/Forward Rendering），提升GPU性能，解决大场景加载、动态光影等复杂问题。 ● 制定3D资产制作规范，提升渲染效率与视觉效果。 ● 研究并应用前沿技术（如DLSS、RTX光线追踪、Nanite虚拟几何体等），推动引擎能力升级。
更新于 2025-09-22