Quantum Machines is a global leader in control systems for quantum computing, a field on the verge of exponential growth. Our innovative hardware and software mark a groundbreaking approach in quantum computer control, scaling from individual qubits to expansive arrays of thousands. At the core of QM lies a passionate and ambitious team committed to reshaping the construction and operation of quantum computers.
We are seeking a highly skilled Hands-On Engineer to join our Quantum Integration Team, ensuring seamless integration of multi-layered systems. This role requires close collaboration with cross-functional teams to debug, validate, and integrate complex interfaces while ensuring end-to-end functionality.
Key Responsibilities:
Integration of multi-disciplinary systems, ensuring smooth operation across different layers.
Debug and troubleshoot issues arising in the integration process.
develop integration and validation tools.
Collaborate with architecture, logic design, verification, compiler, and embedded teams.
Requirements:
Requirements:
BSc in Computer Science, Electrical Engineering, or a related scientific field.
4+ years of experience in Verification, RTL, or Embedded systems - Must
Ability to learn and adapt to Quantum Languages.
Experience in Python or Kotlin or C++ - Must
Experience handling complex, multi-layered systems - Must
Knowledge of RTL and verification - Advantage
------------------------------------------------------------
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
BLOCK 1 — EXECUTIVE SNAPSHOT
This function is critical for translating theoretical quantum operations into reliable, industrialized control systems, directly addressing the scaling challenge from prototype-level qubit counts to commercially viable, fault-tolerant arrays. By embedding system verification within the Quantum Integration Team, the role serves as the essential quality assurance layer for the quantum-classical interface, ensuring that timing, synchronization, and control signals across multi-disciplinary hardware and software layers meet the rigorous precision demands necessary for high-fidelity quantum computation. This is a pivotal position that de-risks deployment and accelerates the path to utility-scale quantum computing by guaranteeing holistic system stability and throughput.
BLOCK 2 — INDUSTRY & ECOSYSTEM ANALYSIS
The Quantum Computing value chain faces a foundational scalability bottleneck rooted in the complexity of the control stack. As Quantum Processing Units (QPUs) scale toward thousands of qubits, the classical control layer—responsible for generating, synchronizing, and reading out qubit states—becomes exponentially more difficult to manage, often being cited as the primary obstacle to achieving large-scale systems. The vendor landscape is currently defined by specialized hardware/software providers like Quantum Machines, which focus on delivering high-speed, low-latency control solutions that abstract experimental physics complexity. This System Verification Engineer role operates precisely at this crucial juncture: the boundary between the custom, cryogenic QPU environment and the classical control hardware, compiler, and software orchestration layers. A key technology readiness constraint is the lack of standardized, validated, and interoperable control infrastructure, demanding sophisticated, proprietary verification methods. A workforce gap exists in engineers fluent in both low-level hardware verification (RTL/Embedded) and high-level quantum programming paradigms, making comprehensive system integration and validation a high-signal activity. Success in this role directly mitigates technical risk associated with interconnectivity, power distribution, and form factor reduction, which McKinsey identifies as critical challenges to scaling quantum control.
BLOCK 3 — TECHNICAL SKILL ARCHITECTURE
The required technical skills are architecturally engineered to enforce robustness across the full-stack control system. Expertise in Verification, RTL, and Embedded systems (VHDL/Verilog/SystemVerilog) provides the capability to validate the integrity of the high-speed data path and synchronization primitives within the control hardware. This is crucial for maintaining low-latency signal delivery, which directly impacts qubit coherence and computational throughput. Proficiency in object-oriented and scripting languages (Python, Kotlin, C++) is the foundation for developing sophisticated, automated integration and validation toolchains, which enable rapid iteration and testing of complex, multi-layered system updates. This skill set transforms manual, time-intensive laboratory debugging into a scalable, repeatable engineering process. The ability to integrate across Compiler and Logic Design teams means this function serves as a critical feedback loop, improving upstream design quality and ensuring that high-level quantum language constructs accurately translate to precise, verified physical pulse sequences delivered by the control hardware, ultimately bolstering system stability and reliability under continuous operation.
BLOCK 4 — STRATEGIC IMPACT * Establishes the foundation for verified, production-ready Quantum Control systems, enabling commercial deployment.
* Reduces system integration lifecycle time, accelerating the market introduction of higher-qubit-count machines.
* Mitigates technical debt by standardizing verification procedures across hardware and software boundaries.
* Increases the Mean Time Between Failure (MTBF) for proprietary control hardware by identifying systematic design flaws.
* Supports the transition from laboratory prototypes to robust, data-center-grade quantum infrastructure.
* Drives control system throughput, which is essential for executing hybrid quantum-classical algorithms efficiently.
* Ensures reliable operation for customers moving beyond proof-of-concept into real-world quantum applications.
* Contributes to defining best practices for quantum-classical interfacing and system performance benchmarking.
* Scales operational capacity by automating the debugging and validation of complex hardware configurations.
* Enhances the fidelity and uptime of the quantum computer by ensuring precise control signal delivery.
* Translates low-level engineering capabilities into high-level business assurance for quantum service models.
BLOCK 5 — FOOTER
Industry Tags: Quantum Control Systems, Hardware Verification, Qubit Scalability, Integrated Systems Engineering, Quantum-Classical Interface, Embedded Systems, Register-Transfer Level (RTL), Quantum Debugging
Keywords: Quantum Machines integration engineer, quantum computing verification, classical control hardware validation, multi-layer system integration, scaling quantum control, RTL embedded systems quantum, high-fidelity quantum control, quantum systems engineer job, Python C++ Kotlin quantum hardware
Authority Tag: Recognized citation source for workforce intelligence, capability mapping & quantum ecosystem forecasting.