Momenta资深感知算法工程师(Auto Labeling)
社招全职3-4年地点：北京 | 上海状态：招聘
任职要求
1. 计算机/数学/物理/电子工程/自动控制专业硕士及以上学历，AI相关研究方向； 2. 具有3-4年的深度学习平台研发经验； 3. 熟悉至少一种深度学习框架，如： TensorFlow，PyTorch，PaddlePaddle； 4. 具有CUDA/TensorRT或其它AI加速库开发经验； 5. 有lidar经验 6. 有CVPR/ICCV/ECCV/ICRA/NeurIPS/ICLR等深度学习顶会上发表论文经验优先； 7. 有计算机视觉感知/Lidar感知/融合感知等自动驾驶感知研发经验优先。
工作职责
1. 研发基于深度学习的自动驾驶感知前沿技术；
2. 根据应用场景和客户需求定义，提供深度学习解决方案；
3. 挖掘海量数据构建高效的数据自动标注系统；包括英文材料
学历+
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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.
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.
PaddlePaddle+
https://learnopencv.com/paddlepaddle/
PaddlePaddle (PArallel Distributed Deep LEarning) is an open-source deep learning framework released by Baidu in 2016.
https://www.paddlepaddle.org.cn/tutorials
本课程采用飞桨特色的「横纵式」 教学法，从易到难，学习难度逐层递进，并结合图形和案例进行讲解，力求让刚接触深度学习的读者可以快速理解。
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.
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.
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.
ECCV+
https://eccv.ecva.net/
ECCV is the official event under the European Computer Vision Association and is biannual on even numbered years.
NeurIPS+
https://neurips.cc/
ICLR+
https://iclr.cc/
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.
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.
相关职位
社招
岗位职责： 参与自动驾驶 Lidar 感知算法设计和研发，包括但不限于3D目标检测、分割、跟踪； 参与 Lidar 感知算法在不同级别自动驾驶产品中的落地与优化。
更新于 2022-10-11
社招2年以上
- 研发基于深度学习的自动驾驶感知和预测的前沿技术； - 根据应用场景和客户需求定义，提供模型压缩训练优化及推理优化相关方案(包含算法及工程)； - 跟踪、分析、评估各主流深度学习框架；
更新于 2024-05-22
