Quantum Machines seeks exceptionally talented people for challenging work with a team full of quantum tech knowledge and enthusiasm to make an impact on the quantum revolution.

If you’re excited about shaping the future of quantum today, join us!

Software Engineer – Application Validation

Stuttgart Germany

Quantum Machines (QM) is a global leader in quantum computing control systems. Through our pioneering hardware and software solutions with 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 technology. 

We are looking for a passionate Software Engineer to join our Application Validation Team, where you will play a key role in developing the infrastructure and frameworks that are critical to the validation of quantum algorithms and systems.

As a Software Engineer in the Application Validation Team, you will be responsible for building the infrastructure and developing the robust framework necessary to validate quantum computing routines. You will work in the analysis of large datasets of measurement data and design software architectures that integrate real hardware with custom build quantum computing languages.

You will also contribute to the development of automated testing systems and CI/CD pipelines, facilitating rigorous and automated validation. This position offers an exciting opportunity to work on cutting-edge quantum computing systems while collaborating with experts across software and hardware domains.

Responsibilities:

  • Framework Development: Design, implement, and maintain a robust framework to validate quantum computing routines on real hardware, ensuring the system is adaptable, efficient, and scalable
  • Software Architecture: Contribute to the design of software architectures that bridge measurement hardware with software, ensuring optimal performance and seamless interaction
  • Algorithm Design: Develop and optimize algorithms to process quantum computing data, ensuring that these algorithms meet performance and accuracy standards
  • Handling Measurement Data: Develop solutions to process and analyze large datasets, including measurement data collected from real time systems. Ensure these datasets are efficiently integrated into the validation framework
  • Automated Testing & CI/CD: Design and implement automated testing systems and CI/CD pipelines to ensure continuous and reliable validation of quantum systems
  • Interdisciplinary Collaboration: Work closely with hardware engineers, quantum physicists, and software developers to understand and implement requirements towards the validation framework

Requirements:

  • M.Sc. or higher in software engineering, mathematics, electrical engineering or an equivalent field
  • At least 5 years of hands-on programming experience
  • Strong expertise in Python, including experience in data manipulation and analysis
  • Solid background in designing software architectures that interact with real hardware, ensuring performance, scalability, and reliability
  • Ability to develop and optimize complex algorithms, especially for data processing and multi unit computing environments
  • Understanding of different compiler architectures, from high-level languages to low-level assembler instructions, and how they relate to hardware execution
  • Ability to work effectively in a multi-disciplinary team environment with a strong desire to learn new concepts in (quantum) computing and adapt to the evolving nature of the field
  • Experience with developing automated testing frameworks and CI/CD processes, especially in a scientific or engineering context- advantage
  • Knowledge of HPC systems, parallel computing, or distributed computing environments- advantage
  • Familiarity with embedded systems integration- advantage
  • Experience with infrastructure or electronics for high-frequency systems, particularly in the context of quantum hardware or related fields- advantage