Quantum Machines · Delft, ZH ·
Designs, builds, and deploys machine learning systems — reinforcement learning, Bayesian inference, and agentic frameworks — that autonomously calibrate and control quantum processors on real hardware. The role is heavily Python-based, integrating ML services into Quantum Machines' quantum control stack (QUA, Qualibrate, OPX1000).
Cartesian · Cambridge, MA
Quantum Systems · Gilching, Bayern, Germany
Wise Pirates · PORTO, Porto, Portugal
expedition-technology · Herndon, USA
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 looking for a Machine Learning Engineer to design, build, and deploy machine learning systems that improve the calibration, control, and operation of quantum processors. In this role, you will work at the intersection of machine learning, quantum physics, and software engineering, translating noisy, non-stationary, safety-critical control problems into ML solutions that run on real hardware in production labs.
You will develop reinforcement learning policies, Bayesian inference methods, and agentic frameworks that make quantum control more autonomous, more sample-efficient, and more robust to drift. This position offers unprecedented exposure to diverse qubit types and quantum architectures, with a tight feedback loop between your models and the systems they steer, and the opportunity to deliver groundbreaking ML-driven solutions to the labs and companies defining the next generation of quantum systems.
Responsibilities:
Nc Group · Berlin