Software Architect

Quantum Machines (QM) is a global leader in quantum computing control systems. Through our pioneering hardware and software solutions based on instruction-based quantum control, we’re revolutionizing how quantum computers are built and controlled. As we stand at the forefront of exponential growth in quantum computing, we’re assembling an elite team that actively shapes the evolution of quantum technologies.

We are seeking an exceptional Software Architect to join our Architecture team and help shape the software infrastructure powering the next generation of quantum computers. As quantum systems grow in scale and complexity, our software brings together quantum control, classical computing, and diverse hardware into a unified platform for developing and running quantum applications.

What you'll do?

In this role, you will define the architecture of a software framework that enables users to build and run applications across CPUs, GPUs, quantum control hardware, and other devices. The framework will provide unified interfaces for coordinating execution, communication, and resource management, supporting workflows such as hybrid quantum-classical computation and automated calibration. You’ll collaborate closely with Product, R&D, and Research teams to translate evolving needs into clear architecture and practical solutions, from concept through production.

Requirements

• BSc in Computer Science, Computer Engineering, Electrical Engineering, or a related field (MSc or PhD is an advantage).
• 7+ years in software development, including 2+ years in software architecture.
• Proven experience architecting complex software platforms or distributed systems, with strong modular design fundamentals and experience defining APIs, SDKs, or developer tools.
• Hands-on experience with Python and a systems programming language such as C++, including concurrent programming and communication across processes through RPC or streaming.
• Experience with workload orchestration and resource management, including service lifecycles and recovery; familiarity with containerized execution and build and deployment workflows.
• Ability to make architectural trade-offs around performance, reliability, observability, and access control in systems spanning multiple services and hardware resources.
• Strong technical communication and collaboration skills, with the ability to turn complex requirements into clear specifications, learn new domains, and guide multidisciplinary teams.
• Experience with GPU computing, high-performance communication, real-time hardware integration, or scientific computing is an advantage.
• Exposure to quantum computing or automated calibration is an advantage.

Preferred Skills

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