Staff Scientist - Quantum Characterization & Benchmarking

IonQ; United States; Remote; USD 150,000 - 190,000; Full time

Job summary

IonQ is seeking a Staff Scientist specializing in quantum characterisation and benchmarking to lead the QCVV team. You will drive the development of novel characterisation and benchmarking protocols for IonQ's quantum processors, guiding their design and optimisation for next-generation error correction architectures.

You will lead cutting-edge research in QCVV, develop scalable benchmarking frameworks, and collaborate closely with experimental and QEC teams to translate theoretical insights

Qualifications

• Seven+ years of research experience in quantum characterisation or benchmarking.
• Strong publication record in quantum information science.

Responsibilities

• Set research direction for characterising IonQ's quantum processors, building scalable benchmarking protocols for multi-qubit systems.
• Publish research in top-tier venues and represent IonQ at conferences.
• Mentor junior researchers and shape the technical direction of the QCVV team.
• Develop theoretical frameworks linking characterisation data to error models for system improvements.
• Collaborate with QEC and compiler teams to inform error correction code selection and decoder design.

Skills

Benchmarking protocols

Randomised benchmarking

Gate set tomography

Character benchmarking

Scalable benchmarking

Representation theory in QCVV

Education

PhD in physics or related field

Job description

Staff Scientist - Quantum Characterization & Benchmarking at IonQ, Bothell, Washington, United States; Boulder, Colorado, United States; College Park, Maryland, United States; Remote, US (remote). A lead-level full time position in the Compute - Architecture team, listed under research.

Role

We are looking for a Staff Scientist specialising in quantum characterisation and benchmarking. You will serve as the technical lead of the QCVV team, driving the development of novel characterisation and benchmarking protocols for IonQ's quantum processors. Your work will directly inform the design and optimisation of next-generation quantum error correction architectures.

In this role, you will lead cutting-edge research in QCVV, develop scalable benchmarking frameworks, and collaborate closely with experimental and QEC teams to translate theoretical insights into measurable system improvements. The ideal candidate is a world-class researcher with deep expertise in quantum benchmarking and the ability to define and drive ambitious technical programmes.

Responsibilities

You will set the research direction for how IonQ characterises its quantum processors, building protocols that scale to many qubits and that connect what we measure to the error models our architects and QEC researchers rely on.

Alongside your own research, you will publish in top-tier venues, represent IonQ at conferences, mentor junior researchers and help shape the technical direction of the QCVV team.

Requirements

To succeed, you will need a PhD in physics, quantum information, mathematics or a related field, and seven or more years of research experience in quantum characterisation, benchmarking or closely related fields. A strong publication record in quantum information science is expected.

You will be able to write, read and debug scientific simulations and prototypes, and bring deep expertise in benchmarking protocols such as randomised benchmarking, gate set tomography and character benchmarking.

You’d be a great fit with

• Deep expertise in benchmarking protocols, such as randomised benchmarking, gate set tomography and character benchmarking.
• Expertise in representation theory as applied to QCVV.
• Experience with scalable benchmarking methods for many-qubit systems.

Responsibilities

• Lead the development of novel, scalable QCVV protocols for multi-qubit quantum processors.
• Design benchmarks sensitive to specific noise types, informed by component-level characterisations and first principles.
• Develop theoretical frameworks connecting characterisation data to actionable error models, such as detector error models.
• Collaborate with the QEC and compiler teams to inform error correction code selection and decoder design.
• Publish research results in top-tier venues and represent IonQ at conferences.