Sygaldry Technologies

Applied AI Scientist, Technology Partnerships (Senior/Principal)

San Francisco, California, United StatesFull timeStaff$200,000 - $300,000 / yearPosted 9 days ago
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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.

THE ROLE

Our AI & algorithms team develops quantum approaches to training, inference, and reasoning, including quantum-native generative modeling. Much of this work runs today on classical hardware at small scale, built so that results transfer directly to quantum processors as they come online.

Increasingly, that research meets real problems. Partner organizations bring workloads from their own domains, and someone has to carry our methods into each one and find out how well they hold. That is this role. You are a computational scientist who takes scoped collaboration and does the technical work: understand the partner's problem well enough to know where our methods can genuinely help, prototype, benchmark against what they already trust, and be the technical voice in the room when results are discussed. Our partnerships managers own the relationships and run the programs; our research scientists develop the algorithms. You produce the evidence.

WHAT YOU'LL WORK ON

Applied Work in Partner Domains

- Assess where our quantum-native generative methods apply to a specific domain: which algorithm, under what assumptions, in which regime it wins, and what would count as evidence

- Build and run the proof-of-concept work, and ada...