Quantum computing is a strategic priority for NVIDIA, and our goal is to help accelerate the entire ecosystem. In this role, you’ll join a rapidly growing Quantum Computing team and work with internal and external teams to define system requirements to enable fault-tolerant quantum computing.

Do you love engineering complex systems for controlling a quantum computer and working at the speed of light with collaborative people and teams all around the world? If yes, we would love to hear from you!

What you'll be doing:

• Collaborate with internal product, research, and engineering teams and external partners to define system requirements to enable fault-tolerant quantum computing

• Develop novel approaches to real-time quantum error correction and calibration supported by rigorous systems analysis for a variety of qubit modalities

• Distill product requirements to technical requirements across hardware, software, and firmware

• Develop test cases supporting technical requirements and review test implementations for correctness and completeness

• Adopt a culture of collaboration, rapid innovation, technical depth, and creative problem solving

What we need to see:

• Bachelor’s degree in Physics, Electrical Engineering, Computer Science, Applied Mathematics, or related engineering field or equivalent experience. Higher degrees also welcome.

• 5+ overall years of post-bachelor’s experience including responsibility for engineering across multiple parts of a complex hardware and software system

• Deep hands-on experience working with real qubits and quantum control systems software

• Passion to drive technology innovations into NVIDIA software and hardware products to support Quantum Computing

Ways to stand out from the crowd:

• Experience with design of quantum control systems and techniques, including communication and networking

• Experience with development of real-time systems and embedded software

• Knowledge of methods of benchmarking quantum computers

• Adoption of AI and ML techniques

• Experience with CUDA and GPUs

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