A rapidly growing quantum technology company is seeking a Machine Learning Engineer to help shape the future of quantum computing. This is a unique opportunity to work at the intersection of machine learning, advanced physics, and software engineering, developing intelligent systems that directly improve the performance and operation of cutting-edge quantum hardware.
What You'll Do
- Design and deploy machine learning solutions for calibration, control, and optimisation of quantum processors.
- Develop reinforcement learning, Bayesian inference, and probabilistic modelling approaches for complex real-world hardware environments.
- Build autonomous frameworks that enable intelligent system control and adaptive calibration.
- Create and maintain Python-based machine learning services and libraries used in production environments.
- Work closely with research teams and end users to deploy, validate, and refine ML-driven solutions on experimental hardware.
- Collaborate with multidisciplinary teams spanning software, hardware, and product development.
What We're Looking For
- MSc or PhD in Machine Learning, Physics, Applied Physics, Quantum Information Science, or a related discipline.
- Strong hands-on experience in machine learning, with expertise in areas such as reinforcement learning, deep learning, or agentic AI systems.
- Excellent Python development skills and experience building production-grade software.
- Proven ability to take machine learning models from concept through deployment in challenging real-world environments.
- Strong understanding of software engineering best practices including testing, version control, and code reviews.
- Excellent communication skills and the ability to work effectively across technical disciplines.
Desirable Experience
- Quantum computing, qubit calibration, quantum error correction, or optimal control.
- Experience in robotics, autonomous systems, hardware-in-the-loop machine learning, sim-to-real environments, or advanced reinforcement learning techniques.