Planckianis developing the core technology to power utility-scale quantum computers.
By design, our chip architecture decouples control lines from qubit count, removing a key bottleneck in scaling. It combines the proven reliability of superconducting circuits with a breakthrough approach to qubit control, paving the way for quantum computers capable of solving the world’s most challenging problems.
We are seeking aQuantum Measurement Engineerto design, implement, and optimize high-fidelity measurement and control of superconducting qubits.
What You'll be doing
- Design, implement, and optimize qubit readout and control chains for superconducting quantum processors
- Develop measurement protocols for qubit characterization (T₁, T₂, Ramsey, echo, RB, readout fidelity, crosstalk, etc.)
- Optimize signal-to-noise ratio and measurement fidelity under realistic hardware constraints
- Develop and maintain experimental control software (Python-based stacks, FPGA or AWG integration)
- Analyze experimental data and compare results with theoretical models and simulations
- Collaborate closely with device physicists, fabrication teams, and system engineers to improve hardware performance
- Contribute to scalable measurement architectures and automation for large-qubit systems
- Document experimental procedures and results clearly for internal and external communication
Requirements
- PhD or MSc in Physics, Applied Physics, Electrical Engineering, or a related field
- At least +5y of strong hands-on experience with superconducting qubits or closely related quantum hardware.
- Practical experience with microwave engineering (GHz electronics, IQ mixers, amplifiers, VNAs)
- Solid understanding of quantum measurement theory and qubit decoherence mechanisms
- Experience operating cryogenic systems, especially dilution refrigerators
- Proficiency in Python for experiment control and data analysis
- Familiarity with lab automation and measurement frameworks
- Ability to debug complex experimental setups across hardware and software layers
Every job has its challenges, and this one is no exception. While many companies gloss over them, we believe in being upfront:
- You’ll face tough situations, especially the classic challenge: people problems. Navigating human dynamics can be tricky and requires patience and empathy.
- Some work is unglamorous, but building a great company means rolling up your sleeves. From strategic decisions to hands-on grunt work, everyone contributes to the heavy lifting.
We're not looking for perfection; we're looking for people who are ready to grow through the hard parts and help us build something that lasts.
What We Offer
- Competitive salary + benefits
- Stock options
- Flexible working hours with hybrid working
- Ego-free, merit-based environment
Planckian is an equal-opportunity employer.
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
The structural evolution of superconducting quantum computing necessitates a specialized tier of engineering focused on high-fidelity qubit control and readout systems. As the industry transitions from exploratory prototypes toward utility-scale architectures, the role of a Quantum Measurement Engineer serves as a critical interface between theoretical device physics and physical system reliability. This function addresses the fundamental bottleneck of qubit decoherence and gate error rates by optimizing the signal-to-noise ratios of cryogenic microwave chains. By standardizing characterization protocols and automation frameworks, these experts ensure that quantum hardware performance remains reproducible and scalable. Market signals from major research hubs indicate that the ability to architect high-throughput measurement pipelines is currently a primary determinant for achieving the error thresholds required for fault-tolerant operation.
The global quantum computing ecosystem is currently navigating a period of hardware maturation characterized by the shift from few-qubit experiments to integrated, multi-qubit processors. Within this environment, superconducting circuits represent a leading modality, yet they face persistent scaling constraints related to wiring density, thermal budgets, and control electronics complexity. Addressing these challenges requires a strategic emphasis on measurement engineering to validate hardware performance against increasingly rigorous benchmarks. The role type is positioned at the center of the hardware enablement layer, where the primary objective is to maximize the extraction of information from quantum states while minimizing environmental interference.
Macro-level analysis of the quantum workforce reveals a significant capability gap at the intersection of microwave engineering, cryogenic system management, and automated data analysis. Organizations are increasingly moving away from manual laboratory tuning toward software-defined, FPGA-based control stacks that allow for real-time feedback and error mitigation. This transition is driven by the need to synchronize internal fabrication cycles with the operational requirements of high-performance computing environments. As national quantum strategies prioritize the development of sovereign hardware capabilities, the demand for specialists who can stabilize the physical-to-logical qubit interface continues to outpace available talent.
Furthermore, the integration of automated characterization suites is becoming a standard requirement for the commercialization of quantum processors. This trend favors the development of modular toolchains that can facilitate the rapid assessment of qubit parameters such as relaxation and coherence times. By establishing these technical baselines, measurement engineers enable the benchmarking of diverse hardware architectures, reducing the systemic risks associated with hardware-specific bottlenecks. As the industry moves toward fault-tolerant regimes, the focus is pivoting toward the optimization of readout fidelities and the mitigation of crosstalk in large-scale arrays.
The capability architecture for this role type centers on the synthesis of microwave engineering, quantum information theory, and experimental automation. At the foundational layer, mastery of GHz-range electronics—including IQ modulation, parametric amplification, and signal processing—is essential for ensuring the integrity of qubit control pulses. This technical proficiency is coupled with a deep understanding of decoherence mechanisms, allowing for the precise diagnosis of noise sources within dilution refrigerator environments. These capabilities are critical for the structural throughput of quantum R&D, as they directly influence the stability and accuracy of gate operations in superconducting processors.
Beyond hardware stabilization, the role facilitates a high-level coupling between device fabrication and system-level performance modelling. This interface ensures that advancements in chip design are immediately validated through rigorous measurement protocols, such as randomized benchmarking and gate set tomography. By standardizing the integration of Python-based experiment control stacks with FPGA hardware, these experts enable a level of operational readiness that allows organizations like Planckian to accelerate their development timelines. This strategic alignment is vital for maintaining the accuracy of the technology roadmap as qubit counts expand toward utility-scale systems.
Accelerates the deterministic progression of superconducting hardware toward fault-tolerant error thresholds
Mitigates systemic risks in quantum processor development by establishing rigorous characterization and calibration benchmarks
Facilitates the transition from manual laboratory tuning to automated, scalable measurement architectures for large-qubit systems
Reduces iteration friction between device fabrication and experimental validation through standardized data analysis pipelines
Strengthens the long-term competitive positioning of hardware providers by securing high-fidelity control over qubit states
Harmonizes theoretical quantum mechanics with the practical constraints of cryogenic and microwave engineering environments
Optimizes the lifecycle of quantum processors through the development of interoperable control software and measurement frameworks
Supports the scaling of quantum hardware adoption by identifying and mitigating crosstalk and noise in complex arrays
Shortens the time-to-market for utility-scale quantum computers by ensuring infrastructure alignment with hardware roadmaps
Improves the reliability of quantum gate operations through the application of advanced signal processing and error mitigation
Protects capital-intensive investments in deep-tech by providing expert technical validation of qubit performance milestones
Enables the strategic orchestration of hardware R\&D efforts across multidisciplinary teams of physicists and systems engineers
Industry Tags: Superconducting Qubits, Quantum Measurement, Microwave Engineering, Cryogenic Systems, Qubit Characterization, Experimental Physics, Quantum Control, Signal Processing, Lab Automation, Dilution Refrigerators
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