Nvidia is hiring a
Director, Quantum Computing Applied Research
At NVIDIA, we’re solving the world’s most exciting problems with our unique approach to accelerated computing. We’re looking for passionate technologists with deep quantum computing domain expertise to lead technical path-finding. As Director for Quantum Computing Applied Research, you'll lead our technical path-finding efforts, working with cross functional teams in Product, Engineering and Applied Research to develop innovative technologies that advance the state of Quantum Computing and intercept NVIDIA products.
The Quantum Computing organization is a small, strong, and visible group both inside and outside of NVIDIA while Quantum Information Science is an exciting area to drive strategy. We need a self-starting leader to continue to grow this area. Do you have the rare blend of both technical and product skills with a passion for groundbreaking technology? If so, we would love to learn more about you!
What you'll be doing:
Lead Quantum Computing technical path-finding, working with cross functional teams in Product, Engineering, and Applied Research.
Represent NVIDIA in Quantum Computing technical consortia and committees.
Discover high impact problems NVIDIA can uniquely solve that create new market paradigms.
Drive technology innovations into NVIDIA software and hardware products to support Quantum Computing.
Speak at relevant scientific, technical and industry conferences.
What We Need To See
Degree in Physics, Computer Science, Chemistry, Applied Mathematics, or related engineering field or equivalent experience (Ph.D. or Masters preferred)
Extensive background in Quantum Information Science with 10+ overall years experience in the Quantum Computing industry
5 years technical leadership experience working in applied research or path-finding for Quantum Computing
World-class communication skills with a demonstrated ability to articulate a value proposition to technical and non-technical audiences
Ways To Stand Out From The Crowd
Hands-on experience in scientific computing, high-performance computing, applied machine learning, or deep learning.
Experience with CUDA and NVIDIA GPUs.
You will also be eligible for equity and benefits.
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