Quantum Machine Learning Engineer (m/f/d)

Role overview Develop quantum machine learning models that use the probabilistic behavior of quantum circuits, then bring promising approaches from research into production software. You’ll work with research and product colleagues to build extensible model components, benchmark them fairly against classical methods, and operate them as part of a customer-facing platform.

Responsibilities - Implement quantum machine learning models and move them from prototypes into maintainable production modules. - Design fair benchmarks against strong classical models and communicate results accurately, including cases where quantum methods do not perform better. - Define component architecture and interfaces so models, backends, and benchmarks can be extended or replaced. - Deploy and operate services, including CI/CD workflows and APIs. - Run experiments using GPU-accelerated simulators, cloud resources, and quantum processing units. - Collaborate on research publications and conference presentations, and help shape the direction of the modeling stack.

Requirements - Practical quantum machine learning and machine learning implementation experience. - Ability to turn research code into tested, reliable, maintainable software. - Experience designing and interpreting model benchmarks. - Familiarity with deployment workflows, service APIs, and scalable experimentation. - The source indicates research experience or publications in QML or ML; a PhD is a plus.

Nice to have - Experience with GPU-based simulation or training, such as PennyLane Lightning GPU, CUDA-Q/cuQuantum, or JAX/PyTorch on GPU. - Hands-on experience with real quantum hardware, or systems programming in C++ or Rust. - Conversational German.

Benefits and work setup Full-time, mid-to-senior role. Munich is preferred, with remote work available within Germany; flexible hours are offered, and Munich-based colleagues are expected to visit the office about once a week. Publishing and conference participation are supported. Other listed benefits include a fitness membership, a work-related AI assistant subscription, and regular team events.