qubitsok.com
Cut Noise. Work Quantum.
Europe, Germany, Ulm
•
Posted 33 days ago
🏢 QC Design
Role Type
Role Focus
Seniority
Employer Type
This role is for a Quantum Error Correction and Fault Tolerance Engineer focused on turning the latest research in fault-tolerant quantum computing (FTQC) into working software prototypes. You will identify relevant FTQC ideas based on customer feedback and implement them in Python for Plaquette™, a design tool used by quantum hardware companies. The role requires collaborating to productionize successful features, ensuring reliability, and actively contributing to the product's future roadmap.
Key Responsibilities
Identify critical Fault-Tolerant Quantum Computing (FTQC) and Quantum Error Correction (QEC) ideas relevant to scalable quantum architectures based on direct customer feedback.
Implement these ideas as working, readable, and testable prototypes using Python.
Collaborate with quantum software developers to turn the most impactful prototypes into production features.
Increase the reliability of the Plaquette software through reproducible comparisons against existing research literature.
Help define the FTQC product roadmap, prioritizing features that deliver value to customers.
Required Skills
Degree (MSc, PhD, or equivalent experience) in physics, computer science, mathematics, or a related field.
Strong background in quantum error correction and fault tolerance.
Ability to analyze research and identify actionable ideas in fault tolerance.
Proficiency in Python and comfort writing structured, extensible research code.
Clear written communication skills for explaining complex concepts.
Technology Tags
The role explicitly focuses on developing tools and prototypes for quantum error correction (QEC).
The primary objective is developing and optimizing fault-tolerant quantum computing (FTQC) architectures.
Proficiency in Python is explicitly required for implementing working prototypes and structured research code.
The role involves evaluating architectures using hardware-realistic noise models and comparison against reference results.
The Plaquette tool includes decoding workflows, requiring implementation and evaluation of decoders.
A strong background in this field is required to understand and implement frontier FTQC ideas.
This foundational QEC code is crucial for the design and exploration of scalable FTQC architectures.
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