Senior Researcher, Quantum Finance Engineering
IonQ · Remote (United States) · Quantum Finance Applications
About this role
IonQ is hiring a senior-level Research Scientist in the machine learning function as a remote position. The posting calls out experience with AWS, Data Structures, Security, Machine Learning. Compensation is listed at $123,191–$161,289 per year.
- Role
- Research Scientist
- Function
- machine learning
- Level
- senior
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Remote (United States)
- Work mode
- Remote
- Department
- Quantum Finance Applications
More roles at IonQ
Job description
from IonQ careersAbout IonQ:
IonQ, Inc. [NYSE: IONQ] is the world’s leading quantum platform and merchant supplier - delivering integrated quantum solutions across computing, networking, sensing, and security. IonQ’s newest generation of quantum computers, the IonQ Tempo, is the latest in a line of cutting-edge systems that have been helping customers and partners including Amazon Web Services, and AstraZeneca achieve 20x performance results and accelerate innovation in drug discovery, materials science, financial modeling, logistics, cybersecurity, and defense. In 2025, the company achieved 99.99% two-qubit gate fidelity, setting a world record in quantum computing performance.
Headquartered in College Park, Maryland, IonQ has operations in California, Colorado, Massachusetts, Tennessee, Washington, Italy, South Korea, Sweden, Switzerland, Canada, and the United Kingdom. Our quantum computing services are available through all major cloud providers, while we also meet the needs of networking and sensing customers across land, sea, air, and space. IonQ is making quantum platforms more accessible and impactful than ever before.
IonQ is seeking a Senior Researcher, Engineering of Quantum Computing for Financial Applications and Algorithms to co-lead the design, development, and implementation of quantum solutions that address high-value use cases in the financial sector. The ideal candidate will bridge deep domain expertise in financial mathematics, quantitative modeling, and optimization with quantum algorithm design and near-term hardware capabilities.