Research Scientist (Quantum AI)

Location: San Francisco, United States; on-site

Salary: $200K–$300K annually, plus equity

Company

hirify.global Technologies builds quantum-accelerated AI servers and systems that combine quantum computing with artificial intelligence to address compute-cost and energy bottlenecks.

What you will do

• Develop research models for scientific prediction, generation, and design across areas such as molecules, materials, proteins, weather, climate, PDEs, and quantum systems.
• Build algorithms and theory for probabilistic inference, uncertainty quantification, optimization, sampling, planning, control, and scientific reasoning.
• Identify AI-relevant workloads and subroutines where fault-tolerant quantum computation can provide structural advantages.
• Develop quantum-native models, hybrid quantum-classical workflows, and benchmarks comparing quantum, classical, and hybrid approaches.
• Translate AI and scientific-computing bottlenecks into quantum resource requirements and inform quantum architecture decisions.
• Prototype systems with Python, JAX, PyTorch, and relevant quantum software frameworks while collaborating with quantum hardware, architecture, and systems teams.

Requirements

• Research record in machine learning, AI, statistics, physics, applied mathematics, computer science, quantum information, or a related field.
• Deep expertise in at least two areas including generative modeling, probabilistic inference, uncertainty quantification, geometric deep learning, graph neural networks, optimization, reinforcement learning, scientific machine learning, quantum algorithms, or quantum information.
• Published research relevant to leading machine learning, AI, physics, or quantum-computing venues.
• Ability to move between theory and implementation by deriving algorithms, building prototypes, running experiments, and communicating results clearly.
• Experience with ML frameworks such as PyTorch and JAX, including efficient inference implementation.
• Ability to work on-site in San Francisco and collaborate with quantum hardware teams.

Nice to have

• Experience with diffusion or flow models, energy-based models, probabilistic programming, Bayesian deep learning, neural SDEs/ODEs, simulation-based inference, or scalable Monte Carlo.
• Experience applying AI to science, including molecular or protein design, drug discovery, materials discovery, climate prediction, quantum chemistry, PDE modeling, robotics, or control.
• Background in graph and geometric learning, equivariant architectures, neural operators, tensor networks, manifold methods, or structured world models.
• Experience with quantum algorithms, computational complexity, quantum simulation, quantum chemistry, fault tolerance, resource estimation, or quantum information theory.
• Experience with CUDA/Triton, distributed training or inference, differentiable simulation, or high-performance scientific computing.

Culture & Benefits

• Grounded, optimistic, rigorous, and collaborative research culture.
• Company-sponsored health coverage for employees and families.
• Visa support whenever possible.
• Meaningful equity alongside competitive compensation.
• Unlimited PTO, company offsites, and crew socials.