NVIDIA AI Infra China 招 Deep Learning 和 Web 工程师

V2EX = way to explore

V2EX 是一个关于分享和探索的地方

现在注册

已注册用户请登录

› 下载 GeForce Experience

› NVIDIA SHIELD

› GPU Ray Tracing

› ShadowPlay

› NVIDIA Unix Driver

这是一个创建于 1895 天前的主题，其中的信息可能已经有所发展或是发生改变。

缺人，急，在线等

如题，我们组正在招算法和前后端工程师，坐标上海，浦东张江。福利待遇管够

有兴趣的欢迎投递简历到 louli 或者我的用户名艾特 nvidia.com

< Web 工程师 JD />

We are now looking for a Web Full-Stack Engineer!

NVIDIA is searching for extraordinary full stack engineers to work on our AI Infra team. Our team is enabling NVIDIA and our customers to more easily scale up machine learning workflows - machine learning at scale require a new vocabulary for organizing and managing data, jobs and users. We are building and optimizing human in the loop pipelines which enable massive state of the art systems in Artificial Intelligence / Machine Learning at Nvidia and for our customers in many application spaces including medical imagery and autonomous driving.

What you will be doing:

You will be collaborating with a diverse team of front and back-end engineers as well as machine learning, deep learning experts.
You will be creating human in the loop and management interfaces at the frontier of what is possible in machine learning today and getting front seat view of the action in this very hot space from a team and a company driving the progress at the cutting edge.

What we need to see:

Golang, Spring Cloud, Python, Node
Knowledge of REST APIs
Web stack backend: Postgres, SQL, MongoDB, redis,
Knowledge of AWS / Aliyun tools and capabilities
Comfortable with a customer focused, high paced environment.
Well versed in agile methodology.
Experience in software shipping cycles (dev, deploy, release, CI) and open-source software dev.
You are highly motivated, passionate and curious about new technologies. You take pride in your work and strive to achieve incredible results and possess excellent communication and planning skills.
Ability to work successfully with multi-functional teams, principals and architects. Coordinates effectively across organizational boundaries and geographies.

Ways to stand out from the crowd:

Understanding of JavaScript/CSS/HTML5, working knowledge of Angular.
Team player, loves to work in a team environment
Native Mandarin, Fluent English

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. Are you a creative and autonomous software engineer with a genuine passion for advancing the state of AI and machine learning across a variety of verticals? Do you love a challenge? If so, we want to hear from you.

# -*- DL 工程师 JD -*-

We are now looking for a Deep Learning Engineer!

NVIDIA is hiring Deep Learning Engineers for its Self Driving Car Deep Learning team. Academic and commercial groups around the world are powering a revolution in artificial intelligence using deep learning techniques running on NVIDIA GPUs, enabling breakthroughs in problems from image classification to speech recognition to natural language processing. Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time. The era of AI has begun.

What you’ll be doing:

Inventing and applying state of the art deep learning algorithms to solve problems related to building autonomous vehicles.
Work on object detection, classification and segmentation based on images, radar and lidar data.
Interaction with various internal product and research teams contributing toward building a self driving car software solution as well as partners and customers

What we need to see:

You have deep expertise in deep learning algorithms, machine learning, or nonlinear optimization.
Excellent programming, software design, and testing skills in Python, C++, or similar languages
Masters or PhD or equivalent experience in Computer Science, Artificial Intelligence, Applied Math, or related field.

Ways to stand out from the crowd:

Experience with deep learning frameworks such as TensorFlow, CNTK, Caffe, Torch, or Theano, especially for computer vision
Participation in deep learning competitions where you finished in the top 5
Experience with data-parallel and/or accelerated computing (CUDA, OpenCL)
Experience with embedded architectures, including DSP and hardware accelerators

GPU computing is the most productive and pervasive platform for deep learning and AI. It begins with the most advanced GPUs and the systems and software we build on top of them. We integrate and optimize every deep learning framework. We work with the major systems companies and every major cloud service provider to make GPUs available in data centers and in the cloud and we create computers and software to bring AI to edge devices, such as self-driving cars and autonomous robots

With deep learning, we can teach AI to do almost anything. New internet services, like Google Assistant, have learned speech from sound and provide a more natural way to access information. Self-driving cars use deep learning to recognize the space the car inhabits, the lanes in which it drives, and the objects to avoid. In healthcare, neural networks trained with millions of medical images can find clues in MRIs that until now could only be found through invasive biopsies. These are just a few examples. AI will spur a wave of social progress unmatched since the industrial revolution.

Nvidia is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you. Come, join our Deep Learning Software team and help us build the real-time, cost-effective computing platform driving our success in this dynamic and quickly growing field.

中文 JD 可以私聊

18 条回复 • 2019-12-01 13:23:21 +08:00