Applied AI Scientist (Senior/Principal)
$200k - $300k • San Francisco • FullTime
Posted 2mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Sygaldry Technologies is pioneering quantum-accelerated AI servers to dramatically speed up AI training and inference, aiming to accelerate the path to superintelligence and address compute cost and energy challenges. Our AI servers integrate multiple qubit types in a fault-tolerant architecture for cost, scale, and speed. This role is within our AI & algorithms team, focusing on applying quantum approaches to AI problems, including generative modeling. You will work on real-world problems by taking scoped collaborations, understanding partner needs, prototyping solutions, benchmarking against existing methods, and communicating technical results.
Responsibilities
- Assess where quantum-native generative methods apply to specific domains, identifying the appropriate algorithm, assumptions, and success criteria.
- Build and run proof-of-concept work, adapting research implementations for relevant domains.
- Validate solutions against partner's trusted reference methods (e.g., molecular dynamics, Monte Carlo, classical solvers, production models).
- Present and refine results in technical working sessions, feeding learnings back into future development decisions.
- Produce evidence through simulation, circuit emulation, or analytic resource models.
- Design robust benchmarks comparing quantum, classical, and hybrid approaches against strong classical methods.
- Utilize internal modeling and simulation environments to demonstrate workload performance on Sygaldry's architecture.
- Extend models to new algorithm workloads and generate supporting documentation for results.
Requirements
- Ability to ship reproducible results and write code daily.
- Strong quantitative skills to rigorously assess results.
- Capability to hold technical conversations with domain experts in unfamiliar fields.
- Comfort assessing the applicability and limitations of quantitative methods.
- Ability to manage multiple engagements concurrently.
- Advanced degree (MS, PhD) in a computational field or equivalent industry experience.
- Strong Python and scientific computing skills (linear algebra, ODE/SDE solvers, sampling, Monte Carlo, uncertainty quantification).
- Experience with generative modeling techniques (diffusion, flow matching, normalizing flows, score-based/energy-based models).
- Familiarity with tensor network methods or other structured representations for high-dimensional problems.
- Applied domain experience in areas like molecular modeling, time-series forecasting, physical simulation, or generative design.
- Technical writing ability and a track record of reproducible research or publications.
- Curiosity about quantum computing (prior experience is a plus but not required).
Benefits
- Visa sponsorship available.
- Competitive salary and meaningful equity.
- Company-sponsored health coverage.
- Company offsites and social events.
- Unlimited Paid Time Off (PTO).