Senior Engineer - Quantum Error Correction Libraries
Indexed description
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
- 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.
- 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.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 28, 2026.
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.
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