NVIDIA's accelerated computing platform has revolutionized HPC and AI, and we have built the cuQuantum SDK to enable quantum computing researchers and framework developers. This role will be part of an engineering team developing, scaling, and optimizing software to accelerate and scale quantum computing and quantum system simulations. Ideal candidates will have experience building simulation software for quantum error correction (QEC) and will have strong affinity for advancing the state-of-the-art in applications of HPC and GPUs to the quantum computing ecosystem. If you are passionate about developing high-performance software and want to help us build libraries to significantly accelerate research and development in this exciting field, we would love to hear from you!
What you will be doing:
Developing innovative algorithms to accelerate simulation of QEC workloads at scale.
Researching, developing and optimizing GPU-accelerated algorithms across multiple hardware generations
Working closely with NVIDIA Research, Developer Technology, and Product Management teams in the areas of quantum computing, HPC technologies, and machine learning
Interacting with external partners and researchers to understand their use cases and requirements
Providing technical leadership and mentorship to other specialists
What we need to see:
Excellent modern C++ and Python programming skills, including, debugging, functional testing, and performance testing.
Proven track record to convert mathematical or research-level algorithms into robust, reusable, and well-documented software primitives.
Expert understanding of QEC and stabilizer formalism, including binary symplectic representations, stabilizer and destabilizer tableaux, Pauli-frame propagation, mid-circuit measurement, and classical control.
Strong understanding of noise models, including Pauli, correlated, and time-dependent noise, as well as exact and approximate representations of non-Pauli noise.
Familiarity with the broader quantum software landscape, including Stim, Qiskit Aer, PennyLane, Cirq, cuQuantum SDK, CUDA-Q, or similar development frameworks.
Strong communication skills and experience collaborating across research, engineering, and product teams.
PhD or MS degree in Computer Science, Applied Mathematics, Physics, Electrical Engineering, or a related scientific or engineering field, or equivalent experience.
8+ years of relevant research or software-development experience.
Ways to stand out from the crowd:
Proficiency in near-Clifford or stabilizer simulation techniques.
Knowledge of QEC code varieties and procedures, such as surface codes, subsystem codes, color codes, quantum LDPC, lattice surgery, and logical-state preparation. Hands-on experience with QEC decoders.
Experience developing performance-critical GPU software using CUDA or a comparable environment.
Proficiency in horizontal scaling across multiple nodes or GPUs using NCCL, MPI, NVSHMEM, or equivalent high-performance communication stacks.
Aptitude for using agentic or AI-supported development tools alongside steadfast dedication to validation, testing, and code review standards.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- Excellent C++ and Python programming skills
- Experience programming for GPUs
- PhD or MSc in Computer Science, Applied Math, Physics, or related field
- 8+ years of experience in relevant field
- Strong collaboration and communication skills
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
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Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
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Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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