[NVIDIA英伟达] 热招解决方案架构师

NVHR

我们是Glassdoor选出的“最佳工作场所”

我们是《人物》选出的“年度关爱公司”

我们是《财富》选出的“全球最受赞赏公司”

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我们这里有无微不至的关爱

我们这里还有“评价最高的CEO”

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我们，就是AI计算的引领者NVIDIA

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春风十里

我们一直在等你

梦想的机会就在眼前

你来不来？

本期热招职位-Deep LearningSolution Architect （解决方案架构师）

该岗位致力于协同客户经理将NVIDIA最新的深度学习/高性能计算解决方案与技术带给我们的客户,帮助客户通过实施NVIDIA技术解决方案来提升整体效率；

工作地点: 北京
上海
深圳

如果您或您身边的朋友有深度学习,无人驾驶或者高性能计算(CUDA)经验，请发送英文简历到tracyw@nvidia.com    Wechat： 1751315121

具体职位描述:

What You’ll Be Doing

• Assist NVIDIA Account Managers in supporting     existing lighthouse accounts and driving new business in those accounts     and new accounts.
• Deliver technical projects, demos and client     support tasks as directed by the Solution Architecture leadership team.
• Provide technical support for GPU system     deployments.
• Be an industry thought leader on integrating     NVIDIA technology into applications built on Deep Learning, High     Performance Data Analytics, Robotics, Signal Processing and other key     applications.
• Be an internal champion for Data Analytics,     Machine Learning, and Cyber among the NVIDIA technical community.

What We Need to See

• 1-3 years’ experience with development and     application of Machine Learning, data analytics, or computer vision work     flows.
• Outstanding verbal and written communication     skills
• Ability to work independently with minimal     day-to-day direction
• Strong Linux skills.
• C/C++/Python/Java/Scala programming     experience
• Experience with parallel programming     development and optimization
• Experience with GPU computing and CUDA     programming
• Strong teamwork and interpersonal skills
• Desire to be involved in multiple diverse     and innovative projects
• Experience using scale-out cloud and/or HPC     architectures for parallel programming
• MS or PhD in Engineering, Mathematics,     Physics, Computer Science, Data Science, Neuroscience, Experimental     Psychology or equivalent work experience.

Ways To Stand Out From The Crowd

• Experience with Deep Learning frameworks and     tools, eg. Digits, Caffe, Torch, TensorFlow.
• CUDA optimization experience.
• Extensive experience designing and deploying     large scale HPC and enterprise computing systems.