Senior Engineer - Quantum Error Correction Libraries

Details

NVIDIA's accelerated computing platform has revolutionized HPC and AI, and CUDA-Q brings accelerated computing to the quantum computing ecosystem. This role focuses on developing, scaling, and optimizing GPU-accelerated simulators for CUDA-Q, NVIDIA's platform for hybrid quantum-classical computing. It combines modern C++ and Python development with quantum computing expertise to turn cuQuantum SDK primitives into robust, high-performance simulation capabilities.

Responsibilities

• Design, develop, and maintain quantum computing simulation components in CUDA-Q.
• Extend CUDA-Q with new simulation methods and optimize existing methods for quantum dynamics and open-system simulation.
• Build software connecting CUDA-Q programs to simulation libraries, including circuit and operator representations, execution interfaces, Python bindings, and resource management.
• Profile and improve end-to-end performance, memory usage, CPU-GPU data movement, and batching across GPU architectures and representative quantum workloads.
• Collaborate with cuQuantum SDK, CUDA-Q, NVIDIA Research, and Product Management teams, as well as external researchers and open-source contributors, to translate use cases into reliable software.

Requirements

• Excellent modern C++ and Python programming skills, including debugging, functional testing, numerical validation, and performance profiling.
• Strong quantum computing foundations, including quantum circuits, linear algebra, measurement, observables, density matrices, and quantum noise channels.
• Hands-on experience implementing or extending quantum simulators, with depth in at least one approach such as state-vector, tensor-network, stabilizer, Pauli propagation, or open-system dynamics simulation.
• Experience developing maintainable software in a collaborative environment using Git, code review, automated builds, and continuous integration.
• Strong communication skills and experience leading technical work 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.

Preferred Qualifications

• Experience with CUDA-Q, cuQuantum SDK, or comparable frameworks and simulators such as Qiskit Aer, Cirq, PennyLane, Stim, or QuTiP.
• Expertise in stabilizer and Clifford simulation, sparse Pauli representations and Heisenberg-picture propagation, tensor-network methods, or quantum master-equation solvers.
• Experience developing performance-critical GPU software with CUDA and scaling simulation workloads across multiple GPUs or nodes using MPI, NCCL, NVSHMEM, or comparable communication libraries.
• Aptitude for using agentic or AI-supported development tools while maintaining detailed validation, testing, and code review standards.

Compensation and Benefits

• Expected base salary for Level 4: USD 184,000–287,500 per year.
• Expected base salary for Level 5: USD 224,000–356,500 per year.
• Eligibility for equity and benefits.
• Applications will be accepted at least until November 16, 2026.
• NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer.