Atomic-precision silicon quantum processors and quantum computing systems
Silicon Quantum Computing designs and fabricates its own silicon quantum chips in Sydney, pairing semiconductor tooling (Electron Beam Lithography, Cadence Virtuoso, Calibre) with a full DevOps and ML stack (Kubernetes, Terraform, PyTorch). Accelerating, engineering-heavy hiring centers on calibration automation, qubit drift prediction and fabrication yield, while NetSuite adoption signals finance operations maturing alongside commercialization.
Silicon Quantum Computing is a privately held quantum computing company founded in 2017 and headquartered in Sydney, NSW. It manufactures silicon chips with atomic precision in-house and builds quantum processors, quantum machine learning chips and simulation systems. The company employs 51–200 people and currently hires in Australia. Its work spans atomic electronics, semiconductor fabrication, device calibration and the software that delivers customer datasets.
SQC uses Electron Beam Lithography, Cadence Virtuoso, Calibre and ANSYS for chip work, FPGA hardware, plus Kubernetes, Terraform, Ansible, Ceph, Python, PyTorch, TensorFlow, and AWS, Azure and GCP. It is adopting NetSuite.
Yes. Hiring is accelerating and heavily weighted toward engineering, mostly mid and senior levels, with smaller openings in HR, finance, legal, marketing and ops, all in Australia.
Current projects include qubit drift prediction models, a real-time calibration service, an FPGA calibration engine, computer vision for device measurement and new fabrication techniques for quantum architectures.
Other companies in the same industry, closest in size
Silicon Quantum Computing's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.