Quantum-AI Postdoctoral Fellow
$90k - $120k • San Francisco • FullTime
Posted 10h ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
AI Research Engineer
About the job
Sygaldry Technologies is developing quantum-accelerated AI servers to dramatically speed up AI training and inference. By merging quantum computing with AI, the company aims to accelerate the development of superintelligence and ensure its efficient and affordable operation. Their unique approach involves integrating multiple qubit types into a single, fault-tolerant architecture to achieve the necessary cost, scale, and speed for advanced AI applications. Sygaldry is at the forefront of new discoveries in physics, engineering, and AI, tackling complex challenges with a grounded, optimistic, and rigorous culture. They are seeking individuals passionate about defining the future at the intersection of quantum and AI and driving its global impact.
Responsibilities
- Investigate and advance state-of-the-art diffusion and score-based generative models, focusing on mathematical efficiency.
- Conduct theoretical analysis of computational bottlenecks in sampling, denoising, and likelihood estimation.
- Develop novel solver methods for diffusion ODEs/SDEs compatible with quantum algorithms.
- Identify mathematical structures in generative models that can benefit from quantum speedup.
- Prototype hybrid quantum-classical workflows for accelerating classical pipelines.
- Benchmark theoretical versus practical advantages of hybrid approaches.
- Publish research findings in top-tier conferences and journals.
- Collaborate with quantum hardware teams to inform future architecture requirements.
- Translate research insights into scalable proof-of-concept implementations for engineering teams.
Requirements
- PhD (or nearing completion) in Computer Science, Physics, Applied Mathematics, or a related field.
- Deep expertise in diffusion probabilistic models, score matching, or related generative methods.
- Understanding of mathematical foundations: SDEs, ODEs, Langevin dynamics, and probability flow.
- Experience with ML frameworks like PyTorch or JAX.
- Ability to write clean, research-grade code.
- Strong track record of research excellence, including first-author publications.
- Excitement for tackling novel problems and questioning assumptions rigorously.
- Familiarity with numerical methods for differential equations.
- Understanding of quantum algorithms and computational complexity (deep quantum expertise not required if ML math is strong).
- Background in high-dimensional probability or stochastic processes.
Benefits
- Access to industrial-scale compute and hardware resources.
- Intellectual freedom of an academic environment.
- Visa sponsorship available.
- Salary significantly above standard academic postdoctoral rates.
- Company-sponsored health coverage.
- Company offsites and crew socials.
- Unlimited PTO.