Join Our Team as a Hardware Validation Engineer at Qblox!
At Qblox, we operate at the frontier of the quantum revolution, we are the leading provider of scalable and modular quantum control stacks that generate the analogue signals essential for controlling and reading out qubits in next-generation quantum computing and networking systems. Our work directly contributes to shaping the future of this revolutionary technology.
Operating across frequencies spanning from DC to the microwave regime (up to 18GHz), our signals must exhibit exceptional performance with minimal noise, temperature drift, and interference.
Your experience as a Hardware Validation Engineer will play a pivotal role in the expansion to our next generation system.
Our R&D team tackles complex challenges, and you will test, characterize, validate and debug high-performance electronic hardware, working at the intersection of high-speed digital, RF, and ultra-low-noise measurement systems.
This role requires deep expertise in circuit analysis, experience with automated test frameworks
and mastery of lab equipment.
Joining Qblox means becoming part of a dynamic, international team where innovation thrives. Collaboration is at the heart of our culture — ideas are shared, creativity is encouraged, and solutions are crafted together. You will have the autonomy to explore, experiment, and make meaningful contributions that directly impact the trajectory of our projects.
If you want to push the boundaries of technology, thrive in a collaborative environment, and play a key role in building the next generation of quantum computing hardware, we’d love to hear from you.
Key Responsibilities
● Create comprehensive test plans based on hardware specifications for characterization
and validation measurements
● Initial board bring-up of new PCBAs
● Debug hardware prototypes, identifying and resolving signal integrity, noise, and
performance issues
● Perform characterization and validation measurements of high-speed digital, RF, and
low-noise analog PCBAs, to ensure all the requirements are met
● Develop and maintain automated test frameworks to increase test coverage and
efficiency
● Collaborate with design, firmware, and software engineers to debug issues, analyze
data, and ensure the design meets requirements`
● Generate and maintain detailed technical documentation and validation reports
● Mentor and guide junior engineers
Skill Requirements
● Bachelor’s or Master’s degree in Electrical Engineering or a related field
Enough about us, what about you?
To really enjoy this role, we expect you will have a background encompassing the following:
- Minimum of 5 years of professional experience
● Solid background int RF circuit design, simulation and measurements
● Mastery of lab equipment (e.g. Oscilloscopes, Spectrum Analyzers, VNAs etc.)
● Proficiency in Python for testing and data analysis
● Ability to debug complex hardware systems at board and system level
● Deep understanding of signal integrity and power integrity principles
● Experience with Altium Designer
● Familiarity with Agile methodology and Jira issue tracking systems
● Strong problem-solving and analytical skills, with attention to detail
● Highly motivated, proactive, and a collaborative team player with a creative “can-do” mentality
● Excellent communication skills in English (full professional proficiency, written and spoken)
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
The maturation of the quantum computing sector depends heavily on transitioning control infrastructure from experimental laboratory benches to reliable, industrial-grade systems. Hardware Validation Engineers occupy a critical stabilization point within the physical enablement layer, systematically confirming that modular control stacks achieve the strict operational thresholds required to manipulate qubit arrays. By verifying signal fidelity across high-frequency domains, this function reduces the physical error rates that limit quantum coherence times and fidelity metrics. Sector-wide efforts continue to address talent and integration challenges in quantum systems, making structured engineering evaluation an essential prerequisite for scalable, fault-tolerant architectures. Consequently, this engineering specialization bridges the translation gap between experimental hardware components and predictable, commercially viable deep-tech systems.
The hardware ecosystem for quantum computing has reached a critical pivot where the primary bottleneck is transitioning from standalone qubit discovery to the scalable orchestration of quantum control systems. Within this value chain, control infrastructure serves as the essential bridge translating digital algorithmic instructions into precise analog waveforms. As systems scale toward larger qubit counts, maintaining signal integrity across dense radio-frequency routing paths requires rigorous, systematic verification frameworks.
Macro-level constraints, particularly the global scarcity of engineering professionals who understand both microwave electronics and quantum mechanical noise profiles, place immense pressure on developmental timelines. Sector-wide efforts continue to address talent and integration challenges in quantum systems, which are compounded by the fragmentation of proprietary hardware interfaces and varying Technology Readiness Levels across different computing modalities. Interoperability across vendor ecosystems demands standardized benchmarking methodologies to mitigate integration risks before capital deployment.
Furthermore, long-term industry viability relies on stabilizing fragile supply chains for specialized radio-frequency and low-noise components. National quantum strategies emphasize that regional leadership in deep tech requires domestic expertise capable of transitioning prototype architectures into repeatable manufacturing pipelines. By shifting the ecosystem focus from speculative breakthroughs to deterministic validation methodologies, the industry secures the baseline stability required to attract enterprise-scale infrastructure investment.
The capability architecture for this role type demands the convergence of ultra-low-noise analog characterization with advanced automated testing frameworks. Expertise in characterizing signal integrity up to microwave regimes is fundamental to identifying the microscopic thermal drift and electromagnetic interference that trigger decoherence in superconducting and spin-based qubit processors. This requires a deep operational familiarity with complex laboratory instrumentation, including vector network analyzers and high-bandwidth oscilloscopes, which serve as the primary diagnostic interfaces for physical layer optimization.
These technical proficiencies are critical for maximizing organizational R&D throughput, as they enable the parallelization of hardware revisions alongside system software development. By establishing deterministic, python-driven automation pipelines, this function replaces manual laboratory testing with high-throughput validation cycles, drastically reducing the time required to qualify new printed circuit board assemblies. This technical interface directly accelerates the feedback loop between circuit design and firmware execution, ensuring that control signals remain stable under the dynamic constraints of active quantum error correction protocols. - Accelerates the deterministic transition of modular quantum control systems from laboratory prototypes to standardized commercial products
- Mitigates systemic signal degradation risks by executing rigorous validation across radio-frequency and ultra-low-noise analog domains
- Facilitates the seamless integration of next-generation hardware control stacks into existing classical high-performance computing infrastructures
- Optimizes developmental iteration cycles through the implementation of highly reproducible automated test and characterization frameworks
- Minimizes physical layer error rates by verifying strict signal integrity tolerances under variable thermal and environmental conditions
- Strengthens supply chain predictability by establishing rigid, objective quality benchmarks for complex electronic component manufacturing
- Enhances the scalable deployment of multi-qubit architectures through the meticulous characterization of high-frequency control interfaces
- Supports cross-functional engineering alignment by providing validated baseline data to design, firmware, and software teams
- Reduces capital allocation friction by ensuring that new hardware iterations meet structural performance requirements prior to manufacturing
- Empowers the standardized benchmarking of control electronics across diverse, fragmenting quantum processor modalities and ecosystems
- Protects intellectual property investments by documenting deterministic circuit behavior and systemic debugging outcomes during bring-up
- Advances global technology readiness levels by stabilizing the critical physical infrastructures required for fault-tolerant computingIndustry Tags: Quantum Control Systems, Hardware Validation, Signal Integrity, Microwave Engineering, Radio Frequency Characterization, Automated Test Frameworks, Low-Noise Electronics, Quantum Ecosystem Value Chain, Deep Tech Infrastructure
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