Senior Quantum Applied Research Scientist, Calibration and Decoding
NVIDIA· Research Staff Member
Hybrid (Redmond, WA), Hybrid (Remote, California), Hybrid (Santa Clara, CA)$192k - $304.8kFull-timePosted 4mo ago
About the role
Senior role at NVIDIA focused on quantum device physics, calibration, and machine learning to enable fault-tolerant quantum computing. Develop real-time, physics-informed AI systems, synthetic data pipelines, surrogate models, and co-optimized calibration-decoding workflows, and scale GPU-accelerated implementations.
Responsibilities
- Research and develop open AI models for quantum system calibration to advance the state of the art and empower the quantum community to build on shared foundations.
- Build physics-informed synthetic data generation pipelines that leverage quantum device models, noise channels, and Hamiltonian characterization to produce high-quality training data for upstream calibration and decoding model development.
- Develop surrogate models of quantum hardware that capture device physics and drift behavior, enabling rapid performance prediction and parameter inference without full experimental overhead.
- Architect performant real-time AI systems that jointly account for calibration state and decoding requirements, co-designing model latency, throughput, and update cadence to meet the demands of fault-tolerant feedback loops.
- Apply reinforcement learning and online learning methods to calibration policy optimization, enabling models that improve continuously from hardware feedback and generalize across device families and modalities.
- Develop GPU-accelerated implementations to ensure the full pipeline scales.
- Communicate research findings and collaborate with academic and industry partners to advance the field, while championing rapid innovation, technical depth, and creative problem solving.
Qualifications
- Masters degree in Physics, Computer Science, Electrical Engineering, Applied Mathematics, or a related field (Ph.D. strongly preferred); or equivalent experience.
- 8+ years of combined experience and high impact in quantum systems and AI/ML research.
- Hands-on expertise in machine learning and deep learning for science or physics, including model architecture design, training at scale, fine-tuning, and evaluation.
- Strong background in quantum device physics and information science, including noise models, error mechanisms, and fault-tolerant quantum systems across one or more qubit modalities.
- Broad understanding of quantum control, such as pulse-level hardware interfaces and classical feedback through software abstractions.
- Excellent communication and collaboration skills.
Skills
Required:Quantum device physicsMachine learning for science/physics
Nice to have:Reinforcement learning
Benefits
- Comprehensive benefits package.
- Equity eligible.
Last updated Sep 18, 2026. Interested? Apply on the company site.
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