Quantum Scientist - Time-to-Solution & Benchmarking

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About this role

Quantum Scientist - Time-to-Solution & Benchmarking Albuquerque, NM, USA 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-

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