
Momenta端到端模型算法工程师-静态元素
社招全职地点:北京 | 苏州 | 上海状态:招聘
任职要求
1. 硕士及以上学历,计算机科学、人工智能、机器人、自动化等相关领域。 2. 精通深度学习在计算机视觉中的应用,熟练掌握目标检测(YOLO、DETR)、语义分割(UNet、DeepLab)、关键点检测等任务。 3. 具备红绿灯/交通标识等静态元素感知的实战经验,熟悉相关数据集(如BDD100K、Mapillary Vistas、COCO)。 4. 熟练使用PyTorch/TensorFlow框架,具备端到端模型从训练到部署的全流程能力。 5. 熟练使用Python/C++,熟悉Linux开发环境及CUDA加速。
工作职责
1. 负责研发面向高精度静态环境感知的端到端深度学习模型,重点覆盖交通信号灯(红绿灯)、交通标识、车道线、路缘、静态障碍物等关键元素的检测与识别。 2. 构建并优化基于多传感器(摄像头、激光雷达、高精地图)融合的静态场景感知算法,确保在复杂城市道路、隧道、强光/弱光等极端场景下的鲁棒性。 3. 主导红绿灯的状态识别(颜色、闪烁、倒计时)及空间定位算法研发,解决小目标检测、遮挡、动态背光等关键技术挑战。 4. 设计端到端模型架构(如BEV感知、Transformer-based模型),实现从原始数据到结构化静态场景输出的高效映射。
包括英文材料
学历+
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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.
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.
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
Linux+
https://ryanstutorials.net/linuxtutorial/
Ok, so you want to learn how to use the Bash command line interface (terminal) on Unix/Linux.
https://ubuntu.com/tutorials/command-line-for-beginners
The Linux command line is a text interface to your computer.
https://www.youtube.com/watch?v=6WatcfENsOU
In this Linux crash course, you will learn the fundamental skills and tools you need to become a proficient Linux system administrator.
https://www.youtube.com/watch?v=v392lEyM29A
Never fear the command line again, make it fear you.
https://www.youtube.com/watch?v=ZtqBQ68cfJc
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.
相关职位
社招3年以上自动驾驶
1. 负责端到端算法模型设计研发和工程落地,包括动静态元素感知,occupancy 感知,障碍物轨迹预测,行为决策等端到端算法; 2. 研发交付通用感知算法模型,具备query-base onemodel多模块交互能力,构建全场景空间感知能力和行为预测能力; 3. 构建端到端算法模型自监督训练框架,探索occupancy预训练空间智能方案,通过数据闭环持续迭代模型能力; 4. 持续提升端到端算法模型中occupancy性能指标,扩展occupancy 在3DGS与worldmodel上的应用。
社招3年以上自动驾驶
1. 负责理想汽车自动驾驶端到端模型方法研发和工程落地,包括但不限于动静态感知/通用障碍物/障碍物预测决策等端到端模型; 2. 负责设计高性能上限,具备量产能力的端到端模型算法,包括但不限于diffusion、VLM等模型算法; 3. 开发高效离线训练框架,以及可实时运行的在线推理框架,优化模型推理性能,研发模型部署工具链和优化工具; 4. 建立云端数据感知/决策联合标注Pipeline、数据挖掘机制以及难样本分析等工具链,利用影子模型挖掘众包数据,通过数据闭环持续选代模型能力。

社招算法序列
1、负责以视觉为主的空中离散要素开发,包括重建其3D信息及与道路结构的绑定信息; 2、负责辅助驾驶中路口通行功能的性能调优及工程落地等工作; 3、参与辅助驾驶泛化的评测集构建以及训练集迭代,保障所负责功能的版本质量。
更新于 2025-08-19