Six Figure Work

Senior Quantum AI Research Scientist, Applied Research

NVIDIA

Company websitenvidia.com (NVIDIA, opens in new tab)

Base salary $192,000  to $304,750

Employer-published annual base salary, USD. Advertised base range in Redmond, WA +1 more

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  • LocationRedmond, WA +1 more
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (8 min ago) · observed since
All places named
  • Redmond, WA
  • Santa Clara, CA

About this job

At NVIDIA, we're solving the world's most exciting problems with our unique approach to accelerated computing. We're looking for a passionate AI research scientist with deep quantum computing expertise to path-find the future of fault-tolerant quantum systems powered by machine learning.

Quantum computing is a strategic priority for NVIDIA, and our goal is to accelerate the entire ecosystem. As a Sr. Applied Research Scientist in Quantum Computing, you will architect and build AI solutions at the heart of fault-tolerant quantum computing—spanning quantum error correction, decoding, calibration, and beyond. You will research and develop open AI models, curated datasets, and rigorous benchmarks that advance the state of the art and empower the broader quantum community. Your research will help translate cutting-edge theory into practice by fine-tuning models for specific quantum error-correcting codes and hardware platforms, while collaborating with multi-functional teams across Product, Engineering, and Applied Research to integrate AI into next-generation Accelerated Quantum Supercomputers!

Do you love developing new technology, enjoy working with collaborative people and teams around the world, and operating at the speed of light? If yes, we would love to hear from you!

What you'll be doing:

  • Design and architect AI/ML models—including deep neural networks, graph neural networks, transformers, and reinforcement-learning agents—for quantum error correction, syndrome decoding, logical operation synthesis, and real-time calibration in fault-tolerant quantum systems.

  • Develop cutting-edge AI techniques for quantum computing that contribute to NVIDIA's open model efforts across the quantum ecosystem.

  • Help create high-quality, large-scale datasets for quantum error correction and quantum system characterization, including simulated and hardware-derived syndrome data, enabling the community to train and evaluate AI models at scale.

  • Collaborate with quantum hardware teams to collect and structure hardware-derived training data, enabling domain-adapted models that improve over time as hardware matures.

  • Co-design AI solutions with quantum hardware and software teams, ensuring decoders and calibration models meet latency and throughput requirements for real-time operation inside fault-tolerant feedback loops.

  • Communicate research findings through top-tier venues and collaborate with academic and industry partners to advance the field, while championing a culture of rapid innovation, technical depth, and creative problem solving.

What we need to see:

  • Degree in Computer Science, Physics, Applied Mathematics, Electrical Engineering, or a related field (Ph.D. strongly preferred); equivalent demonstrated experience also considered.

  • 8+ years of combined experience in quantum computing and/or AI/ML research, with a track record of high-impact contributions in at least one of these domains.

  • Deep expertise in machine learning and deep learning—including model architecture design, training at scale, and evaluation—applied to scientific or engineering problems.

  • Strong background in Quantum Information Science, including quantum error correction, fault-tolerant protocols, and quantum noise models.

  • Excellent communication skills and the ability to collaborate effectively with multi-functional teams across research, engineering, and product.

Ways to stand out from the crowd:

  • Hands-on experience developing learned decoders or AI-driven calibration systems for quantum hardware (superconducting qubits, trapped ions, or other platforms).

  • Experience with large-scale model training and fine-tuning—including parameter-efficient fine-tuning (LoRA, QLoRA, adapters) and domain adaptation for scientific AI models.

  • Proficiency with CUDA and NVIDIA GPU programming for accelerating quantum simulation, AI model training, or real-time decoding workloads.

  • Experience with high-performance computing (HPC) environments and distributed training frameworks (e.g., PyTorch Distributed, Megatron-LM, or JAX pmap) for large-scale quantum AI workloads.

  • Passion to drive AI innovations into NVIDIA software and hardware products that support the broader quantum computing ecosystem.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

#LI-Hybrid

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 192,000 USD – 304,750 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 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.

Source: NVIDIA on Workday · View original posting (opens in new tab)

Pay in context

This role's base floor ($192,000) is above 86% of the 357 Data & ML roles in Washington listed on this site; 5 others list the same floor. Their median floor is $143,700; the middle half runs from $136,000 to $168,100.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 8, 2026.

This range next to 6 other live NVIDIA roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live NVIDIA roles with the nearest advertised base floor
RolePublished base
Senior Quantum AI Research Scientist, Applied Research (this listing)$192,000 - $304,750
Manager, Field Application Engineering - OEM Support$192,000 - $304,750
Senior Quantum Applied Research Scientist, Physics Modeling$192,000 - $304,750
Principal Applied Quantum Research Scientist$192,000 - $304,750
Senior Research Scientist, Security and Privacy$192,000 - $356,500
Senior Research Scientist, EDA and AI$192,000 - $356,500
Senior Robotics Research Scientist$192,000 - $356,500

Same $100K to $400K scale as every card. All NVIDIA roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-10-30
Where this pay comes from

Location as the employer wrote it: US, WA, Redmond • US, CA, Santa Clara

base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 192,000 USD – 304,750 USD.

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.

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