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About the Role

This role involves applying quantum-native generative methods to specific partner domains. You will understand partner problems, prototype solutions, benchmark against existing methods, and present technical findings. You will produce evidence through simulation, emulation, and analytic models, designing benchmarks and using internal tools to demonstrate workload performance on Sygaldry's architecture.

Responsibilities

• Assess where quantum-native generative methods apply to a specific domain, including algorithm choice, assumptions, winning regimes, and evidence criteria.
• Build and run proof-of-concept work, adapting research implementations to relevant domains.
• Validate results against partner's reference methods (e.g., molecular dynamics, Monte Carlo, classical solvers, production models).
• Present and refine results in technical working sessions.
• Incorporate learnings (model scales, data characteristics, evaluation criteria) into future development decisions.
• Produce evidence via approximate simulation, circuit emulation, and analytic resource models.
• Design robust benchmarks comparing quantum, classical, and hybrid approaches under realistic assumptions.
• Utilize the internal modeling and simulation environment to illustrate partner workload performance on Sygaldry's architecture.
• Extend models to new algorithm workloads and generate supporting artifacts for published and partner-facing results.

Requirements

• Ability to write code daily and ensure results are reproducible.
• Sufficient quantitative depth to accurately assess results.
• Capacity to hold technical conversations with domain experts in unfamiliar fields.
• Comfort in assessing the applicability and limitations of quantitative methods.
• Ability to manage multiple concurrent engagements effectively.
• Advanced training (MS, PhD) in a computational field (physics, chemistry, applied mathematics, computational biology, engineering) or equivalent industry experience.
• Strong Python and scientific computing skills, including linear algebra, ODE/SDE solvers, sampling and Monte Carlo methods, and uncertainty quantification.
• Experience with generative modeling techniques (diffusion, flow matching, normalizing flows, score-based or energy-based models).
• Exposure to tensor network methods or other structured representations for high-dimensional problems.
• Applied domain experience in molecular or materials modeling, time-series forecasting, physical simulation, or generative design.
• Technical writing ability and a track record of reproducible research artifacts or collaborative publications.
• Curiosity about quantum computing (prior experience is a plus but not required).

Skills

• Python
• Scientific computing
• Linear algebra
• ODE/SDE solvers
• Sampling and Monte Carlo methods
• Uncertainty quantification
• Generative modeling
• Diffusion models
• Flow matching
• Normalizing flows
• Score-based models
• Energy-based models
• Tensor network methods
• Structured representations
• Molecular modeling
• Materials modeling
• Time-series forecasting
• Physical simulation
• Generative design
• Technical writing
• Reproducible research
• Quantum computing

Location

• San Francisco - On Site

Work Type

• On Site
• Occasional travel

Experience Level

• Scientist who ships
• Advanced training (MS, PhD) or equivalent depth

Education Level

• MS
• PhD

Salary/Compensations

• $200,000 - $300,000

Benefits

• Visa Sponsorship
• Competitive salary
• Meaningful equity
• Company-sponsored health coverage
• Company offsite
• Casual crew socials
• Unlimited PTO

About the Company

• Sygaldry Technologies is building quantum-accelerated AI servers to exponentially speed up training and inference for AI.
• We are integrating quantum and AI to accelerate the path to superintelligence and address rising compute costs and energy bottlenecks.
• Our AI servers combine multiple qubit types within a fault-tolerant architecture for cost, scale, and speed in advanced AI applications.
• We pioneer new domains in physics, engineering, and AI, tackling hard challenges with a grounded, optimistic, and rigorous culture.
• We are looking for individuals ready to define the intersection of quantum and AI and drive its global impact.
• 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 publish our algorithm work when it meets our bar, and we lean into agentic AI tools as part of daily workflows.
• We're looking for scientists, engineers, and operators to forge new paths with us at the intersection of quantum and AI.

Equal Opportunity

• We encourage applications from candidates with diverse backgrounds.
• We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
• We encourage you to apply even if you do not believe you meet every single qualification.
• If you don't think this role is right for you, but you believe that you would have something meaningful to contribute to our mission, please reach out at letsbuild@sygaldry.com.