below marketmost similar roles pay hereabove market
This role pays more than
91%
of similar roles. Most pay
$177,250–$216,250
— the blue band above.
At the midpoint, this role pays about
$236k
versus about
$197k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1623 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1110 roles with salary data.
The Senior Engineer - Quantum Error Correction Libraries will join an engineering team focused on developing, scaling, and optimizing software to accelerate quantum computing and quantum system simulations. The role involves developing innovative algorithms to accelerate simulation of quantum error correction workloads at scale and optimizing GPU-accelerated algorithms across multiple hardware generations. Key responsibilities include converting mathematical research-level algorithms into robust software primitives and providing technical leadership. Required skills include modern C++ and Python, expert understanding of stabilizer formalism, binary symplectic representations, and noise models. Candidates should be familiar with the quantum software landscape including Stim, Qiskit Aer, PennyLane, Cirq, cuQuantum SDK, and CUDA-Q. The work addresses the technical challenge of accelerating quantum error correction research through high-performance computing and GPU technologies.
What does a Engineer earn in California?
Median $199500 from 103 postings across 31 companies.
Develop innovative algorithms to accelerate the simulation of quantum error correction (QEC) workloads at scale.
Research, develop, and optimize GPU-accelerated algorithms across multiple hardware generations.
Convert mathematical or research-level algorithms into robust, reusable, and well-documented software primitives.
Implement QEC stabilizer formalism, including binary symplectic representations and Pauli-frame propagation.
Model various noise types, including Pauli, correlated, and time-dependent noise.
Develop performance-critical GPU software using CUDA or comparable high-performance computing environments.
Scale software horizontally across multiple nodes using NCCL, MPI, or NVSHMEM communication stacks.
Provide technical leadership and mentorship to other specialists within the engineering team.
What we're looking for
Excellent modern C++ and Python programming skills, including debugging, functional testing, and performance testing.
Proven track record of converting 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/destabilizer tableaux, and Pauli-frame propagation.
Strong understanding of noise models, including Pauli, correlated, and time-dependent noise.
Familiarity with the broader quantum software landscape, including Stim, Qiskit Aer, PennyLane, Cirq, cuQuantum SDK, or CUDA-Q.
PhD or MS degree in Computer Science, Applied Mathematics, Physics, Electrical Engineering, or a related field, or equivalent experience.
8+ years of relevant research or software-development experience.
Proficiency in near-Clifford or stabilizer simulation techniques (preferred).