Staff Scientist - Quantum Applications - Chicago
Confirmed live in the last 24 hours
IonQ
Compensation
$167,808 - $219,704/year
Job Description
About IonQ:
IonQ, Inc. [NYSE: IONQ] is the world’s leading quantum company delivering solutions to solve the world’s most complex problems. IonQ’s newest generation quantum computers, IonQ Tempo and IonQ Forte Enterprise, are the latest in cutting-edge systems that have been helping customers and partners such as Amazon Web Services, AstraZeneca, and NVIDIA achieve 20x performance results. The company achieved 99.99% two-qubit gate fidelity, setting a world record in quantum computing performance in 2025.
The company is accelerating its technology roadmap and intends to deliver the world’s most powerful quantum computers with 2 million qubits by 2030 to accelerate innovation in drug discovery, materials science, financial modeling, logistics, cybersecurity, and defense. IonQ’s advancements in quantum networking position the company as a leader in building the quantum internet.
We are looking for a Staff Scientist in Quantum Applications to provide technical leadership and hands-on execution across complex, multi-stakeholder quantum application efforts in developing next-generation quantum algorithms and applications on IonQ’s trapped-ion quantum computers. This role is central to IonQ’s mission to translate quantum computing advances into real-world scientific and commercial impact. You will be a quantum algorithms subject matter expert, work closely with internal teams, customers, and partners, drive high-impact applications, and support a new landmark initiative with the University of Chicago.
Responsibilities:
- Provide technical direction and architectural guidance across multiple quantum application efforts, including establishing best practices for benchmarking, performance analysis, and solution design
- Develop, implement, and optimize novel quantum algorithms that will make scientific and commercial impact in areas such as computational chemistry, optimization, and machine learning
- Work with customers and partners to define and solve problems of real-world interest using IonQ trapped-ion quantum computers
- Discover innovative solutions, rigorously benchmark their performance, and publish results in high-impact, peer-reviewed journals and conferences
- Help shape team culture and create a lasting impact by supporting an initiative that delivers new scientific discoveries and innovation
You’d be a good fit with:
- 8+ years of professional experience in quantum computing, applied algorithms, or advanced scientific computing, or an equivalent combination of education and experience
- Demonstrated expertise in Python and/or C++, and deep, hands-on experience with Qiskit or similar quantum SDKs
- Hands-on experience developing and optimizing quantum algorithms in areas such as computational chemistry, optimization, and machine learning
- Track record of delivering innovative quantum solutions demonstrated through peer-reviewed manuscripts, invited talks, open-source repositories, licenses, publications, and/or patents
- Deep understanding of key quantum computing concepts and the ability to articulate deeply technical ideas to diverse audiences, ranging from scientists and engineers to business leaders and community stakeholders
- Demonstrated ability to lead technical efforts from problem definition to solution delivery, with strong collaboration and communication skills
You’d be a great fit with:
- Ph.D. in computer science, mathematics, engineering, physics, or a closely related field
- Experience with end-to-end ownership of complex quantum application efforts, including the ability to mentor interns and provide technical guidance to junior team members
- Experience with variational quantum algorithms and hybrid quantum-classical workloads spanning CPUs, GPUs, and QPUs
- Experience with developing high-performing algorithms optimized for NISQ systems as well as error-corrected and fault-tolerant quantum computers
- Demonstrated experience with quantum algorithm resource estimation, performance benchmarking, and scaling analysis
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