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[上海]英伟达半导体科技(上海)有限公司

  1. 发布时间:2020-07-29
  2. 工作地点:上海
  3. 职位类型:全职
  4. 来源:前程无忧(51JOB)
  5. 职位:Deep Learning Engineer
职能类别:大学/大专应届毕业生

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:

1. Inventing and applying state of the art deep learning algorithms to solve problems related to building autonomous vehicles.

2. Work on object detection, classification and segmentation based on images, radar and lidar data.

3. 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:

1. You have deep expertise in deep learning algorithms, machine learning, or nonlinear optimization.

2. Excellent programming, software design, and testing skills in Python, C++, or similar languages

3. Masters or PhD or equivalent experience in Computer Science, Artificial Intelligence, Applied Math, or related field.

Ways to stand out from the crowd:

1. Experience with deep learning frameworks such as TensorFlow, CNTK, Caffe, Torch, or Theano, especially for computer vision

2. Participation in deep learning competitions where you finished in the top 5

3. Experience with data-parallel and/or accelerated computing (CUDA, OpenCL)

4. 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.



公司简要介绍:

公司名称:英伟达半导体科技(上海)有限公司
公司类型:外资(欧美)
公司介绍:NVIDIA—AI计算公司中的领导者
我们定义了现代计算机图形
我们拥有世界第 一大游戏平台GEFORCE
我们助力世界上运行速度最快的超级计算机
1999年,从行业第 一个图形处理单元(GPU)GeForce 256开始,我们始终深耕技术,寻求创新和突破。最新的NVIDIA A100 GPU更是搭载全球***的7纳米处理器NVIDIA Ampere GPU架构问世,实现了迄今为止***的GPU性能飞跃。
这是每一位NVIDIA工程师的匠人之心。
我们从图形计算起航,拥抱AI和加速计算的浪潮,为当代达·芬奇和爱因斯坦打造专属计算机,帮助他们看见并创造未来。
这是NVIDIA工程师团队开辟的创新之路。
我们看到超级计算的适用范围正在迅速扩展,未来全球信息经济的重心将从服务器转移到新型的强大且灵活的数据中心。以数据中心为计算单元的新时代已经来临。
我们感知到身边越来越多的事物可以是智能的、云连接的,并且基于一个可以为几乎每个行业构建富有想象力的服务的平台。万物智能的变革已经开始。
我们已经开始加速从芯片到CPU和GPU的连接方式,更希望与你一起将其推及至整个软件堆栈,最终实现跨数据中心的性能提升。
加入我们!让我们一起推动高性能计算的下一个时代,让我们在关乎世界却只有我们能把握的棘手新机遇中并肩前行!


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