
文远知行W5算法工程师(感知算法/模型优化)-物流车-北京/上海/广州/深圳
社招全职地点:广州 | 北京 | 上海 | 深圳状态:招聘
任职要求
1、熟悉深度学习。有相关端到端项目/论文经验者优先 2、有较好的计算机基础。ACM竞赛获奖者优先 3、有较好的数理基础 二、感知模型优化: 岗位职责: 1、负责移植优化ai drive算法模型,部署到w5平台 2、针对模型出现的问题提供相应解决方案 1.熟悉模型推理优化基本原理,例如算子优化,融合,混合精度部署、模型量化、蒸馏、剪枝优化等 2.熟悉常见的AI模型推理引擎或了解编译优化技术 ,例如TensorRT,T…
登录查看完整任职要求
微信扫码,1秒登录
工作职责
算法工程师(感知算法/模型优化)-物流车-北京/上海/广州/深圳 一、感知算法: 负责迁移适配aidrive在W5上面的表现
包括英文材料
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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/
推理引擎+
https://www.youtube.com/watch?v=_dvk75LEJ34
https://www.youtube.com/watch?v=XtT5i0ZeHHE
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.
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.
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.
还有更多 •••
相关职位
暂无相关职位