Quantum Scientist - Time-to-Solution & Benchmarking

Location: Albuquerque, New Mexico USA

Department: Quantum Applications

Summary

QuEra Computing is seeking a Quantum Scientist to develop system- and algorithm-level performance models for large-scale neutral-atom quantum computers. This role focuses on translating device- and architecture-level models into quantitative estimates of algorithmic fidelity, runtime, and time-to-solution for representative quantum workloads.

Working at the interface of quantum algorithms, architecture and benchmarking, you will analyze how hardware constraints and effective error models impact end-to-end computational performance. You will develop system-level performance and runtime models that map device and architecture characteristics to algorithmic success probability, throughput, and time-to-solution. You will collaborate closely with hardware theory, experimental, and application development teams. Your work will directly support internal design decisions and external benchmarking efforts, including participation in programs such as DARPA’s Quantum Benchmarking Initiative (QBI). The ideal candidate combines deep theoretical understanding with practical data-driven insight.

Qualifications

• 5+ years of experience in performance modeling, simulation, or analysis of quantum systems or other complex computational/physical systems.
• Strong background in quantum information science, computational physics, or a closely related quantitative discipline.
• Proficiency in numerical modeling and data analysis using Python or Julia.
• Demonstrated ability to analyze experimental or simulated data and correlate results with abstracted models.
• Strong written and verbal communication skills for technical documentation and cross-disciplinary collaboration.

Preferred Qualifications

• Experience with benchmarking or performance modeling in quantum computing platforms (neutral atoms, ions, superconducting qubits, or similar).
• Experience developing or using abstracted error and performance models to evaluate system- and algorithm-level behavior.
• Prior participation in federally funded research programs (e.g., DARPA, DOE) or large collaborative research efforts.
• Track record of publications or technical contributions related to system-level performance analysis or benchmarking.

QuEra is committed to cultivating a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

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