ML Research Scientist - Quantum Accelerated Generative Models

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 engineering the conditions for it to scale efficiently and operate affordably. 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.

Generative AI is transforming what's computationally possible—but it's also exposing the limits of classical hardware. Diffusion models produce extraordinary results, yet their iterative sampling and high-dimensional score estimation create computational bottlenecks that scale poorly.

We believe quantum computing offers a path through these bottlenecks. As an ML Research Scientist, you'll work at the frontier of generative modeling and quantum acceleration, developing the theoretical foundations and practical implementations that connect these fields. You'll identify where quantum approaches can provide genuine advantage in generative workflows—not incremental improvements, but structural speedups rooted in the mathematics of these models.

Generative Model Architecture & Efficiency

• Advance state-of-the-art diffusion and score-based generative models
• Analyze computational bottlenecks in sampling, denoising, and likelihood estimation
• Develop and benchmark novel solver methods for diffusion ODEs/SDEs

Quantum-Classical Integration

• Identify mathematical structures in generative models amenable to quantum speedup
• Prototype hybrid workflows where quantum subroutines accelerate classical pipelines
• Rigorously benchmark theoretical versus practical advantage in realistic workloads

Research to Production

• Translate research insights into scalable implementations
• Collaborate with quantum hardware teams to inform architecture requirements
• Build systems that make quantum-accelerated generation accessible to practitioners

• Have deep expertise in diffusion probabilistic models, score matching, or related generative methods
• Understand the mathematical foundations: SDEs, ODEs, Langevin dynamics, probability flow
• Are experienced with ML frameworks (PyTorch, JAX) and efficient inference implementation
• Question assumptions and validate with rigor, following interesting threads wherever they lead
• Communicate complex ideas clearly across research communities
• Are excited to work on problems no one has solved before

• Published research on diffusion models, score-based generation, or neural ODE/SDE methods
• Experience optimizing sampling efficiency (DDIM, DPM-Solver, consistency models, etc.)
• Familiarity with numerical methods for differential equations
• Understanding of quantum algorithms and computational complexity
• Background in high-dimensional probability or stochastic processes

Your work accelerates the path to quantum superintelligence. Each quantum component integrated, each AI model enhanced, each instruction set optimized brings us closer to a future where intelligence and quantum mechanics are inextricably intertwined. We're not building incremental improvements - we're creating exponential transformations that will make AI more affordable, sustainable, personalized, and fundamentally more capable.

We’re building the infrastructure for quantum superintelligence and pioneering new domains at the intersection of physics, engineering, and AI. At Sygaldry, curiosity and intellectual courage drive our work. We approach ambitious challenges with a grounded, optimistic, and rigorous culture and know that kind people build the strongest teams. We prioritize mission over ego and collaborate openly with a strong sense of shared purpose.

We dream big, yet we execute with a love of detail. We’re…