About Us
QuantWare is building the world’s most powerful quantum processors to solve humanity's greatest challenges. We do this with our unique VIO™ technology, the only QPU architecture that breaks the hardware barriers that have held quantum computing back, unlocking the path to MegaQubit quantum processors.
With VIO, we are paving the way for the hyper-scale quantum computers that will change the world. And delivering on that vision demands people who don’t shy away from tackling the hardest challenges of our time. That’s where you come in!
We are seeking a Quantum Measurement and Calibration Engineer – Automated Calibration to join our Calibration Software team. In this role, you will sit at the intersection of Quantum Physics and Software Engineering. Your mission is to build scalable, automated QPU bring-up software. Rather than running manual measurement scripts, you will focus on developing production-grade Python software that automates device pre-screening, single- and two-qubit gate and readout calibrations, and continuous recalibration routines. You will work as a core individual contributor alongside Software Engineers, Experimental Physicists, and Production teams to make bringing up a QuantWare QPU fast, reliable, and repeatable.
What you’ll be doing
- Automated Calibration Software: Implement, improve, test, and maintain automated Python software to rapidly characterise and calibrate large-scale QPUs, including resonator spectroscopy, crosstalk matrices, single- and gates, 2-qubit gate calibration, and readout optimization.
- Code Architecture & Quality: Write, review and maintain modular Python code adhering to modern software practices (automated testing with PyTest, CI/CD, documentation, and version control).
- Ownership: Take complete ownership of software functionality – from the initial concept through coding, validation, review and integration.
- Collaborate: Collaborate closely with the internal users of the code base (including in Processor Development and Production) to gather needs, feedback and continuously improve features and calibration workflows.
Your Profile
Education & Background: PhD (or Master’s degree with 2+ years of equivalent industry experience) in Physics, Quantum Information, Electrical Engineering, or Computer Science.
- Qubit Measurement: 2+ years of hands-on experience in cryogenic measurement of multi-qubit superconducting quantum processors, including 2-qubit gate calibration.
- Python Programming: Strong proficiency in Python, with a proven track record of writing clean, modular, and maintainable code for data acquisition, automation, or scientific pipelines.
- Software Engineering: Working knowledge of software engineering best practices, including object-oriented design, version control (Git), code reviewing, and testing frameworks.
- Automation Mindset: Strong drive for eliminating manual measurement overhead, building robust automation scripts, and improving software quality for hardware bring-up.
- Collaboration & Communication: Thrives in a multidisciplinary scale-up environment, bridging experimental quantum physics cleanly with production software engineering.
Don't tick every box? Apply anyway. We know great candidates don't always follow a straight path, and we value diverse experience, perspectives, and ways of thinking. If this role excites you and you believe you can make an impact, we'd love to hear from you!
What We Offer:
At QuantWare, you’ll be part of a high-performing team of world-class experts in an ambitious, fast-moving environment. From day one, you’ll have the trust, tools, and support to do your best work. Here’s what you can expect:
Competitive salary - A salary that reflects the impact and importance of the role (and of course 8% holiday allowance)
Pension that’s built to last - A generous and future-proof pension plan that includes partner and dependent coverage.
Flexibility built on trust - We focus on outcomes. Work flexibly, in a hybrid setup, with an open vacation policy that lets you manage your time
Personal growth - We invest in your L&D, with a budget available to each team member, dependent on their individual ambitions, development needs, and performance
A connected team - We make space to celebrate wins together, with team events, offsites, and spontaneous moments that bring us closer
Diversity & Inclusion at QuantWare
We’re an ambitious company, not only for our goals but also to become an even more diverse and inclusive team. We know this helps us with better decisions, more innovation, and strengthens our culture. In particular, we’d love to see more women in the quantum industry!
So if you’re a female talent, excited about this opportunity but don’t meet every single requirement, we still encourage you to apply.
As part of our recruitment process, candidates may be required to undergo pre-employment screening.
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
The scaling of superconducting quantum processing units (QPUs) faces a critical operational bottleneck in characterization, verification, and recalibration routines. Quantum Measurement and Calibration Engineers specializing in automated calibration serve as the core bridge between physical quantum hardware dynamics and automated software enablement pipelines. As physical qubit counts expand, manual characterization protocols become mathematically intractable, introducing significant downtime in cryogenic testing systems. Automating QPU bring-up protocols directly mitigates testing throughput limits, accelerating device evaluation cycles across commercial fabrication lines. Market signals from sector reports emphasize that scaling beyond NISQ-era hardware hinges on software-driven calibration to maintain high-fidelity gate operations. Consequently, this engineering specialization functions as an essential stabilization node within the deep-tech infrastructure, ensuring repeatable processor performance for downstream cloud integration.
Within the broader quantum computing value chain, measurement and automated calibration engineers occupy a critical intersection between physical hardware fabrication, control electronics, and low-level software stacks. As the sector transitions from laboratory prototypes to commercially viable QPUs, hardware developers face mounting pressure to standardize characterization metrics across multi-qubit chips. The operational reality of cryogenic environments introduces parameter drifts, crosstalk, and decoherence, making automated and adaptive recalibration routines imperative for persistent system availability.
Scale-up initiatives are constrained by the sheer complexity of multi-qubit state space mapping. Traditional manual sweep procedures create significant operational lag, directly impacting hardware deployment timelines and raising the cost per calibrated qubit. Addressing this efficiency gap requires transitioning bespoke physics laboratory scripts into production-grade automation infrastructure. Industry observations highlight that modular software testing, automated data pipelines, and robust version control are as critical to hardware progression as underlying physical coherence times.
System-level integration is further complicated by the fragmentation of control electronics and software architectures across the commercial landscape. Organizations such as QuantWare and other hardware pioneers depend on streamlined characterization workflows to deliver reliable, standard-compliant QPUs to system integrators. Establishing robust, continuous calibration pipelines ensures that quantum hardware can be integrated into high-performance computing environments with minimal maintenance overhead, maintaining continuous operational readiness.
The technical architecture for automated calibration relies on a cross-disciplinary integration of experimental quantum physics, signal processing, and enterprise-grade software engineering. At its foundation, this domain requires expertise in multi-qubit superconducting measurement techniques, including microwave spectroscopy, readout fidelity optimization, and two-qubit gate parameter tuning. Translating these physical phenomena into scalable software demands advanced proficiency in Python-based automation, object-oriented design, PyTest frameworks, and continuous integration pipelines. These software capabilities ensure that characterization routines run deterministically, handling real-time data acquisition, noise characterization, and matrix manipulation with low latency. Interface capabilities must extend smoothly across hardware abstraction layers, bridging physical cryogenic instrumentation with low-level drivers and upper-level scheduling software. Such structural integration minimizes execution overhead, ensures data integrity across testing cycles, and allows experimental insights to be rapidly converted into maintainable software updates. Ultimately, these integrated capabilities drive the throughput, repeatability, and reliability of complex quantum hardware architectures. - Accelerates the transition from laboratory characterization scripts to enterprise-grade QPU bring-up automation
- Reduces operational downtime in cryogenic testing facilities through continuous software-driven recalibration routines
- Enhances physical gate fidelity standardization across large-scale multi-qubit superconducting processors
- Streamlines the translation of experimental physics methodologies into production-level software modules
- Mitigates scaling bottlenecks associated with manual multi-qubit characterization and crosstalk mapping
- Stabilizes hardware performance metrics for end-users relying on continuous quantum cloud accessibility
- Optimizes hardware testing throughput, decreasing the total time-to-market for novel processor iterations
- Facilitates modular integration between physical cryogenic control electronics and low-level software stacks
- Improves data reliability across hardware manufacturing pipelines through automated testing and validation routines
- Strengthens cross-functional execution by aligning hardware development objectives with software engineering protocols
- Protects capital investments in hardware fabrication by ensuring predictable, repeatable QPU operational benchmarks
- Expands total operational yield by identifying defective physical components early in the automated pre-screening phaseIndustry Tags: Superconducting QPUs, Quantum Measurement, Automated Calibration, QPU Bring-Up, Cryogenic Measurement, Quantum Control Hardware, Quantum Software Engineering, Gate Calibration, Crosstalk Mitigation, Micro-architecture Testing
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