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Our Team

Leaders in AI for Quantum Computing

San Francisco, CA

We are a team of ambitious, deep-tech engineers building the AI systems that operate and scale quantum computers. Our mission is to transform these quantum computers into reliable, commercially useful machines that anyone can use.

Meet Our Team

Brandon has spent half a decade developing AI for quantum computing in silicon. He was previously a postdoctoral researcher at Oxford, where he published four papers in Nature journals, including work on high-fidelity hot-silicon-qubit architectures, and helped develop the first AI algorithms that automatically form a qubit in a semiconductor chip. Brandon holds an MEng in Materials Science and a PhD from Oxford.

Joel founded Conductor after leaving his PhD at Oxford on machine learning for scaling quantum computers. Previously, he built full-stack, machine-learning–based control software for superconducting qubits at QuantrolOx, following machine learning and research roles at Quantum Motion, C12, and the London Centre for Nanotechnology. Joel holds an MSci in Physics from University College London.

Joyce was previously a Department of Energy Graduate Research Fellow at Fermilab, where she built routines collecting 300+ hours of superconducting qubit data. She has authored more than 10 publications and developed expertise across the entire quantum stack, from fabricating devices to qubit measurement and automation. Joyce holds an MS in Materials Science and a PhD from Cornell.

View our open positions

7 open roles · San Francisco & Albuquerque

Open Roles

Don't see a role that fits or are you a potential partner? Reach out anyway, we're always looking to build with exceptional people.