Senior Quantum AI Research Scientist, Applied Research

Responsibilities

• 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.

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