Senior Quantum AI Research Scientist, Applied Research
NVIDIA is hiring a Senior Quantum AI Research Scientist, Applied Research. It pays $192k-$305k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Builds AI ●●●● is how Level rates this research scientist role: the job is building AI systems.
- The listed pay starts close to the typical research scientist posting on Level.
- Tools and skills the posting cites include PyTorch, JAX and fine tuning.
- Level classifies it as a senior role.
- Level lists 2,700+ other open roles at NVIDIA.
AI in this role
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.How we rate this
Senior Quantum AI Research Scientist, Applied Research at NVIDIA rates 100 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in research scientist jobs at this level
Pay
- This job starts at
- $192k
- Typical research scientist job
- $192k
This posting starts close to the typical research scientist job. See research scientist jobs
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Tell me about a research question you investigated. What did you find?
- What are the limits of PyTorch that you've run into, and how did you work around them?
- What's a project where you used JAX hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: Fine-tuning, AI Research, PyTorch, and JAX. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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