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AI-enabled cyber defense in quantum and post-quantum contexts * Trustworthy, resilient, and policy ... D. in computer science, cybersecurity, electrical and computer engineering, mathematics, physics ...

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Quantum Ai Engineer information

What is a Quantum AI Engineer?

A Quantum AI Engineer is a professional who combines expertise in quantum computing and artificial intelligence to develop algorithms, models, and software that leverage the power of quantum mechanics for advanced machine learning and data analysis tasks. These engineers work on designing and optimizing quantum algorithms, integrating them with AI frameworks, and exploring new ways to solve complex problems that are difficult for classical computers. They often collaborate with physicists, computer scientists, and data scientists to create innovative solutions in fields like cryptography, optimization, and materials science.

What are the key skills and qualifications needed to thrive as a Quantum AI Engineer?

To thrive as a Quantum AI Engineer, you need a strong background in quantum computing, machine learning, linear algebra, and programming, often backed by an advanced degree in computer science, physics, or a related field. Familiarity with quantum programming languages (like Qiskit or Cirq), classical AI frameworks (such as TensorFlow or PyTorch), and experience with quantum hardware or cloud platforms is typically required. Exceptional problem-solving skills, critical thinking, and the ability to communicate complex concepts clearly are vital soft skills in this role. These competencies are essential for developing innovative solutions at the intersection of quantum computing and artificial intelligence, driving progress in a rapidly evolving technological landscape.

What are some typical challenges Quantum AI Engineers face when integrating quantum algorithms with existing AI systems?

Quantum AI Engineers often encounter challenges when bridging quantum computing with traditional AI frameworks. One key difficulty is translating classical AI algorithms into quantum-compatible formats, which requires a deep understanding of both quantum mechanics and machine learning principles. Additionally, the current limitations in quantum hardware mean engineers must optimize algorithms for noise and limited qubit counts while ensuring meaningful AI outcomes. Collaboration with data scientists and hardware specialists is essential to troubleshoot these integration hurdles and advance scalable quantum AI solutions.

What are popular job titles related to Quantum Ai Engineer jobs?

For Quantum Ai Engineer jobs, the most frequently searched job titles are:

Infographic showing various Quantum Ai Engineer job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution.

Senior Quantum AI Research Scientist, Applied Research

Redmond, WA • On-site

Nvidia Corporation
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidia Corporationexternal

$110K - $140K/yr

Full-time

Re-posted 21 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies

Job description

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 the pay of employees in similar positions. The base salary range 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 May 25, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.

What Nvidia employees say

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Hours and flexibility

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

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