Research Scientist - Frontier AI/ML & Quantum Algorithms

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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About this role

Research Scientist - Frontier AI/ML & Quantum Algorithms San Francisco | OnSite ABOUT SYGALDRY Sygaldry Technologies is building quantum-accelerated AI servers to exponentially speed up training and inference for AI. By integrating quantum and AI, we're accelerating the path to superintelligence, and addressing the problem of rising compute costs and energy bottlenecks. Sygaldry AI servers combine multiple qubit types within a single, fault-tolerant architecture to deliver the combination of cost, scale, and speed necessary for advanced AI applications. We pioneer new domains in physics, engineering, and AI, tackling the hardest challenges with a grounded, optimistic, and rigorous culture. We're looking for individuals ready to define the intersection of quantum and AI and drive its profound global impact. ABOUT THE ROLE Frontier AI is moving toward scientific reasoning and design: molecules, materials, proteins, weather, climate, dynamical systems, quantum devices, and controlled physical systems. These domains expose deep computational bottlenecks in sampling, probabilistic inference, optimization, simulation, uncertainty quantification, inverse design, planning, and control. Sygaldry is building quantum-accelerated AI systems for this next era. We are looking for a Research Scientist who can help define Quantum AI: not just quantum machine learning, but the broader study of how fault-tolerant quantum computation can transform the primitives of learning, inference, reasoning, prediction, geometry, and control. In this role, you will work at the intersection of frontier AI/ML, quantum algorithms, scientific machine learning, and hardware-software co-design. You will identify where quantum computation can provide genuine structural advantage for AI workloads, develop new theoretical and empirical frameworks,

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