Full-Time

Senior Quantum Software Engineer

Posted on 5/16/2026

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$152k - $287.5k/yr

+ Equity

Company Historically Provides H1B Sponsorship

Remote in USA + 3 more

More locations: Canada | Santa Clara, CA, USA | United States

Remote

Category
Software Engineering (2)
,
Required Skills
Python
REST APIs
C/C++
Requirements
  • Ph.D. in Quantum Computing, Physics, Computer Science, or a related field (or equivalent experience).
  • 3+ years of experience.
  • Strong proficiency with C++ and/or Python languages, with experience in GPU-accelerated and parallel programming models.
  • Solid Background in numerical linear algebra (SVD, QR, low-rank approximations, truncation strategies) and their use in tensor network algorithms.
  • Shown experience working on quantum simulation techniques, in particular any of Tensor Networks, MPS, PEPS, Tree Tensor Networks, State-Vector, Stabilizer formalism. With proven ownership of large-scale projects.
  • Excellent communication and interpersonal skills, with the ability to collaborate effectively across multidisciplinary teams.
Responsibilities
  • Build, develop, and maintain HPC-quantum libraries and APIs in C++ and Python, with a strong focus on tensor network–based algorithms and representations.
  • Translate innovative quantum research concepts into production-ready, industry-grade software that integrates seamlessly into NVIDIA’s quantum–HPC ecosystem.
  • Take ownership of new functionality from concept to productization, including design, implementation, testing, debugging, performance tuning and documentation.
  • Drive opportunities to improve library quality, performance, scalability, and maintainability through thoughtful re-architecture and modern software engineering practices.
  • Collaborate closely with product management, architects, and internal and external partners to understand user workflows, define requirements, and contribute to technical roadmaps.
Desired Qualifications
  • Proficiency and experience with quantum algorithms, hybrid quantum–classical workflows and quantum programming frameworks such as CUDA-Q, Qiskit, PennyLane, Cirq, QTip, Stim, or Braket is a strong plus.
  • Solid foundations and practical involvement in Quantum Error Correction, Noise-aware and Error-mitigated simulation, Quantum numerical methods.
  • Experience in analyzing, benchmarking, and optimizing software across CPU and GPU architectures, demonstrating skills in performance profiling and scalability analysis.

NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

Simplify Jobs

Simplify's Take

What believers are saying

  • Agentic AI spending is accelerating, lifting data center revenue and inference demand.
  • Hyperscaler capex remains massive, with NVIDIA positioned at the center of buildouts.
  • Photonic and edge computing investments open adjacent infrastructure markets beyond traditional chips.

What critics are saying

  • AMD, Alphabet, and custom silicon pressure NVIDIA pricing and share in AI accelerators.
  • TSMC dependence exposes NVIDIA to Taiwan disruptions, export controls, and capacity bottlenecks.
  • China export restrictions permanently shrink a major end market and encourage domestic rivals.

What makes NVIDIA unique

  • CUDA and full-stack software create sticky developer lock-in around NVIDIA GPUs.
  • Blackwell GPUs dominate AI training and inference workloads across hyperscale data centers.
  • Vera CPUs extend NVIDIA beyond GPUs into a new $200 billion market.

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