
哈啰感知算法专家/工程师
社招全职3年以上技术地点:上海状态:招聘
任职要求
1、学历与专业背景:硕士及以上学历,计算机科学、电子工程、应用数学、自动化等相关专业。 2、技术能力: 2-1编程技能力:精通C++/Python,熟悉Linux环境开发,具备嵌入式系统优化经验者优先。 2-2算法基础:熟练掌握点云处理(PCL库)、滤波算法(卡尔曼滤波)、目标检测模型(PointPillars)及多传感器融合理。 2-3深度学习框架:至少熟悉PyTorch或TensorFlow,了解模型压缩与部署(如ONNX、TensorRT)。 3、项目经验:需具备3年以上激光雷达感知算法开发经验,主导过自动驾驶项目落地,熟悉ROS/QNX系统,有高精地图构建或SLAM经验者优先。 4、管理与软技能:具备团队管理经验,能制定技术路线并协调跨部门资源。要求逻辑清晰、抗压能力强,良好的沟通与问题解决能力。
工作职责
1、激光雷达感知算法开发与优化。负责自动驾驶场景中激光雷达感知算法的设计、开发和迭代,包括3D目标检测、点云分割、目标跟踪、可行驶区域识别等。需结合深度学习框架(如PyTorch、TensorFlow)优化模型性能,并完成算法上车部署。 2、前沿技术研究与预研。跟踪国际最新研究成果(如PointNet++、PointPillars、CenterPoint等模型),探索无监督/弱监督学习、强化学习等方向在感知领域的应用,推动技术落地。 3、团队管理与跨部门协作。负责技术文档编写、团队任务分配及进度把控,与系统集成、测试、规划模块工程师协作,确保感知算法与整车系统的兼容性和性能优化。 4、数据管理与模型迭代。主导数据标注规则制定、数据挖掘及模型评测,分析badcase并优化算法性能。需熟悉CUDA、TensorRT等加速工具,提升模型在嵌入式平台的运行效率。
包括英文材料
学历+
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
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.
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
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/
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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.
ONNX+
https://github.com/onnx/tutorials
Open Neural Network Exchange (ONNX) is an open standard format for representing machine learning models.
[英文] Introduction to ONNX
https://onnx.ai/onnx/intro/
This documentation describes the ONNX concepts (Open Neural Network Exchange).
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.
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.
ROS+
https://www.youtube.com/watch?v=92Zz5nnd41c&list=PLk51HrKSBQ8-jTgD0qgRp1vmQeVSJ5SQC
https://www.youtube.com/watch?v=HJAE5Pk8Nyw
Ready to learn ROS2 and take your robotics skills to the next level?
https://www.youtube.com/watch?v=MWKnMPX0Yjg&list=PLU9tksFlQRircAdEplrH9NMm4WtSA8yzi
Do you want to know more about ROS the Robot Operating System?
SLAM+
https://docs.mrpt.org/reference/latest/tutorial-slam-for-beginners-the-basics.html
[英文] SLAM for Dummies
https://dspace.mit.edu/bitstream/handle/1721.1/119149/16-412j-spring-2005/contents/projects/1aslam_blas_repo.pdf
A Tutorial Approach to Simultaneous Localization and Mapping
https://ouster.com/insights/blog/introduction-to-slam-simultaneous-localization-and-mapping
SLAM is an essential piece in robotics that helps robots to estimate their pose – the position and orientation – on the map while creating the map of the environment to carry out autonomous activities.
[英文] What Is SLAM?
https://www.mathworks.com/discovery/slam.html
How it works, types of SLAM algorithms, and getting started
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