What are the responsibilities and job description for the Quantum Software Engineer position at Quantum Machines?
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
- At least 5 years of hands-on programming experience in Python – 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.