Define, implement, test and maintain new electrical characterization methods, measurement protocols, and data analysis routines. Proactively identify opportunities for improving existing measurement workflows. Design, implement, and maintain automated data acquisition, instrument control, and processing pipelines in a high-level language, applying machine learning and AI methods where appropriate to maximize measurement throughput and reproducibility. Communicate results, insights and recommendations clearly to multidisciplinary audiences, enabling data-driven decisions across teams. Contribute to and uphold best practices in our codebase, documentation, data quality, reproducibility, and experiment traceability. Model and maintain safety and security practices and compliance with policies. Embody our culture and values. Doctorate in Physics, Engineering, or related field AND experience in industry or in a research and development environment, could include completion of a post doctoral research position OR Master's Degree in Physics, Engineering, or related field AND solid experience in industry or in a research and development environment OR Bachelor's Degree in Physics, Engineering, or related field AND proven experience in industry or in a research and development environment OR equivalent experience. Applied experience in electrical characterization and tuning of quantum devices (e.g. spin qubits, superconducting qubits, etc.) Proficiency in instrument control, experiment automation and data analysis in a high-level language (e.g. Python). Ability to work in an AI-first environment and leverage AI tools to drive innovation and efficiency. Demonstrated ability to work effectively in cross-functional, collaborative technical teams, communicate to a interdisciplinary audience and translating complex data into actionable insights. Self-motivation, ownership mindset, and the ability to deliver results in a dynamic and rapidly evolving environment. A track record of solving problems and driving clarity in ambiguous R&D settings. Doctorate in Physics, Engineering, or related field AND solid experience in industry or in a research and development environment, could include completion of a post doctoral research position OR Master's Degree in Physics, Engineering, or related field AND solid experience in industry or in a research and development environment OR Bachelor's Degree in Physics, Engineering, or related field AND in-depth experience in industry or in a research and development environment OR equivalent experience. Experience applying machine learning and/or AI models to data analysis, experiment automation, or scientific workflows. Experience in electronic transport measurements on semiconductor devices. Experience in characterization of superconducting devices. Experience with radio-frequency measurement techniques. Experience with cryogenic measurements and operating dilution refrigerators. Basic understanding of git and version-controlled collaborative software development practices. Experience building automated, production-quality data pipelines or analysis systems. These requirements include, but are not limited to the following specialized security screenings:
QUANTUM ROLE CONTEXT | Appended by Quantum.Jobs v2
Role context:
This role exists to bridge experimental quantum hardware research and automated measurement operations. Positioned between device physicists, software engineering teams, and laboratory operations, the function focuses on characterization protocols and instrument control infrastructure. By standardizing test procedures, automated data collection, and processing pipelines, personnel in this position ensure consistent evaluation of quantum hardware devices. This operational support enables multidisciplinary research teams to analyze device behavior efficiently and accelerate development cycles for experimental technology platforms.
Quantum ecosystem relevance:
The position directly supports the testing and verification layer of quantum hardware engineering. Reliable measurement techniques, radio-frequency controls, and cryogenic testing pipelines are essential for evaluating physical qubit performance, including spin and superconducting systems. By applying automation and data analysis methods to characterization workflows, individuals in this role enable research organizations to improve measurement throughput and data reproducibility. This systematic testing infrastructure helps validate underlying hardware designs, supporting broader efforts to scale quantum processing architectures.
Capability signals:
- Expertise in electrical characterization and tuning of physical quantum devices
- Proficiency in automated instrument control and data processing using high-level programming
- Demonstrated experience conducting measurements in cryogenic and dilution refrigerator test environments
- Ability to integrate machine learning methods into experimental analysis pipelines
- Track record of maintaining version-controlled software and software engineering best practices
