Senior Quantum AI Research Scientist, Applied Research

Nvidia

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Redmond, WASanta Clara, CA
Salary
$192,000–$304,750 / yr
Employment
Full-time
Posted
159 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $211k
This role $248k
$148k $322k
below market most similar roles pay here above market

This role pays more than 78% of similar roles. Most pay $175,000–$246,500 — the blue band above. At the midpoint, this role pays about $248k versus about $211k 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.

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At a glance

TL;DR · Senior Quantum AI Research Scientist, Applied Research

As a Senior Quantum AI Research Scientist in the Applied Research team, you will architect and build AI solutions at the heart of fault-tolerant quantum computing. Your primary responsibilities include designing and building AI models for quantum error correction, syndrome decoding, logical operation synthesis, and real-time calibration. You will develop open AI models, curated datasets, and rigorous benchmarks to advance the state of the art. Key technologies and skills include deep neural networks, graph neural networks, transformers, reinforcement-learning agents, and proficiency with CUDA, PyTorch Distributed, and JAX pmap. You will work on the technical problem of translating cutting-edge theory into practice by fine-tuning models for specific quantum error-correcting codes and hardware platforms to meet latency and throughput requirements for real-time operation.

What you'll do

  • Design and architect AI/ML models for quantum error correction, syndrome decoding, and real-time calibration.
  • Develop open AI models and curated datasets to advance the state of the art in quantum computing.
  • Create high-quality, large-scale datasets from simulated and hardware-derived syndrome data for community use.
  • Collaborate with hardware teams to collect and structure training data for domain-adapted models.
  • Co-design AI solutions that meet specific latency and throughput requirements for real-time feedback loops.
  • Fine-tune models for specific quantum error-correcting codes and diverse hardware platforms.
  • Communicate research findings through top-tier venues and academic partnerships.

What we're looking for

  • Degree in Computer Science, Physics, Applied Mathematics, Electrical Engineering, or a related field (Ph.D. strongly preferred).
  • 8+ years of combined experience in quantum computing and/or AI/ML research with a track record of high-impact contributions.
  • Deep expertise in machine learning and deep learning, including model architecture design, training at scale, and evaluation for scientific 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.
  • Hands-on experience developing learned decoders or AI-driven calibration systems for quantum hardware (preferred).
  • Experience with large-scale model training, fine-tuning, and domain adaptation for scientific AI models (preferred).
  • Proficiency with CUDA, NVIDIA GPU programming, and high-performance computing distributed training frameworks (preferred).

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