Quantum Machines is looking for a Quantum software Engineer to work closely with customers to design, optimize, and troubleshoot advanced quantum control workflows on real quantum hardware. In this role, you will serve as a technical bridge between customer use cases, experimental requirements, and robust software solutions, ensuring customers successfully deploy and scale quantum experiments using Quantum Machines’ platform.
This position combines strong software engineering practices with hands-on experimental intuition. You will translate complex quantum workflows into reliable, maintainable, and customer-ready solutions, while collaborating closely with internal product, R&D, and hardware teams.
Responsibilities:
- Work directly with customers to understand experimental goals, constraints, and system architectures
- Design, implement, and optimize quantum control workflows tailored to customer applications
- Troubleshoot complex software, system-level, and experiment-integration issues on real quantum hardware
- Provide clear technical guidance, best practices, and documentation to enable customer success
- Develop and maintain Python-based application code, tools, and reference examples
- Contribute to scalable and maintainable software architectures for quantum control systems
- Apply solid software engineering practices, including version control, testing, and code review
- Collaborate cross-functionally with product, R&D, hardware, and software teams to relay customer feedback
- Balance fast, pragmatic solutions that unblock customers with long-term, sustainable engineering improvements
Requirements:
- At least 5 years of hands-on programming experience – Must.
- M.Sc. in Computer/ SW Engineering, Physics, Applied Physics, Quantum Information Science, or a related field. Equivalent industry experience in SW engineering, System Engineering, and experimental quantum computing will also be considered.
- Strong proficiency in Python, including experience with scientific, experimental, or systems-oriented codebases.
- Solid understanding of software engineering fundamentals, including software architecture and Git-based workflows.
- Strong problem-solving skills with a customer-focused mindset.
- Ability to work independently while collaborating effectively in a multidisciplinary team.
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
The Quantum Software Engineer is a critical function at the interface layer, structurally necessary to translate nascent quantum capabilities into executable, stable workflows for end-users. This role accelerates the Technology Readiness Level (TRL) of quantum control systems by ensuring robust software interfaces can manage the complexity of physical quantum hardware operation. Bridging the gap between physics-centric hardware teams and application-centric customers, this position is pivotal in de-risking commercial deployment and minimizing the friction points that impede broader sector adoption of control-stack solutions. The scarcity of professionals operating at this technical nexus underscores its strategic importance in scaling the quantum workforce pipeline.
The role type resides at the lower end of the quantum software stack, focused specifically on hardware enablement and control signal generation, as opposed to high-level algorithm design or application-layer development. It addresses a persistent challenge in the quantum value chain: the operational gap between quantum processing units (QPUs) and standard classical IT environments. Vendor fragmentation across the hardware-control ecosystem necessitates specialists capable of standardizing complex pulse-level sequences into reproducible software abstractions. Furthermore, the iterative nature of quantum experimentation requires rapid feedback loops and troubleshooting capabilities, placing this role at the core of debugging system-level integration issues that span both cryogenic hardware and embedded software. Current industry focus lies on bridging classical and quantum capabilities at scale, and these interface engineering roles are foundational to achieving reliable QPU utilization rates across distributed research and industrial access models.
The technical architecture for this specialization hinges on control plane abstraction and systems-level programming expertise. Proficiency in scientific computing environments, particularly Python for automation and data analysis, is essential for constructing, validating, and maintaining control flows. This role leverages software engineering principles—version control, defensive coding, testing frameworks—to industrialize experimental quantum control sequences, moving them beyond bespoke laboratory scripts. Crucially, it involves understanding the precise timing and physical constraints of the target QPU (Superconducting, Trapped Ion, Neutral Atom, etc.) to optimize pulse-level fidelity and minimize decoherence errors via sophisticated control systems such as the Quantum Machines OPX platform. This capability accelerates throughput and reproducibility, directly impacting the overall performance metrics delivered to external users. * Elevates the operational stability of next-generation quantum computing platforms.
* Accelerates the industrialization of complex quantum experimental protocols.
* Reduces technical debt associated with customized hardware-software integrations.
* Increases QPU utilization rates across diverse end-user research environments.
* Defines best practices for reliable and scalable quantum control workflow deployment.
* Shortens the iteration cycle for hardware calibration and performance optimization.
* Strengthens the critical interface between physical systems engineering and high-level programming.
* Unlocks new application domains requiring precise, low-latency quantum execution.
* Mitigates vendor-specific integration friction for emerging quantum hardware users.
* Drives maturity in quantum software tooling standards and system architectures.
* Enables robust benchmarking and performance monitoring of quantum operations.
* Expands the talent pipeline capable of operating full-stack quantum infrastructure.Industry Tags: Quantum Control Systems, Quantum Software Enablement, Quantum Hardware Interfacing, QPU Calibration, Cryogenic Computing Software, Scientific Python Stack, Quantum Technology Readiness Level, Full-Stack Quantum Engineering
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