GPU-Accelerated Quantum Computing Libraries Lead

NVIDIA; New York (NY); On-site; USD 184,000 - 357,000; Full time

Job summary

NVIDIA in New York is seeking a senior software engineer to join the quantum computing effort, focusing on GPU-accelerated algorithms and scalable quantum circuit simulations. You will design, implement, and optimize high-performance software with MPI and multi-GPU setups, collaborating with NVIDIA Research, Developer Technology, and Product teams.

The ideal candidate has 8+ years in C++/Python, strong hardware-aware optimization, and a PhD or MSc in CS/Physics or related field.

Qualifications

• 8+ years of experience in software engineering or research.
• Proven track record developing scientific software or HPC systems for quantum simulations.
• Excellent C++ and Python programming and software design skills, including performance test design.

Responsibilities

• Research and develop GPU-accelerated algorithms across multiple hardware generations.
• Develop scalable quantum circuit simulations and HPC algorithms.
• Collaborate with NVIDIA Research, Developer Technology, and Product teams in quantum computing, HPC, and ML.
• Interact with external partners to understand use cases and requirements.
• Provide technical leadership and guidance to other engineers.
• Analyze performance and optimize multi-GPU/multi-node implementations.

Skills

C++ programming

Python programming

software design

communication

documentation

leadership

Education

PhD or MSc in Computer Science / Applied Math / Physics

Tools

MPI programming

GPU programming

hardware-aware optimization

Job description

NVIDIA in New York is seeking a senior software engineer to join the quantum computing effort, focusing on GPU-accelerated algorithms and scalable quantum circuit simulations. You will design, implement, and optimize high-performance software with MPI and multi-GPU setups, collaborating with NVIDIA Research, Developer Technology, and Product teams.

The ideal candidate has 8+ years in C++/Python, strong hardware-aware optimization, and a PhD or MSc in CS/Physics or related field.