Job Description
Shape the future of computation at Nexus Quantum Labs, where we're pioneering quantum systems that will redefine industries by 2026. We seek a visionary Quantum Computing Architect to design next-gen quantum processors and hybrid quantum-classical workflows. Join our interdisciplinary team at the intersection of physics, computer science, and AI to solve previously impossible challenges in cryptography, materials science, and optimization. Our Austin hub offers state-of-the-art facilities and unparalleled collaboration opportunities with leading researchers and industry partners.
This role demands both theoretical excellence and practical implementation skills. You'll develop quantum error correction protocols, optimize quantum algorithms for real-world applications, and contribute to our roadmap for fault-tolerant quantum computing. We offer competitive compensation, equity, and the chance to leave an indelible mark on technological history.
Responsibilities
- Design scalable quantum processor architectures and error correction frameworks
- Develop hybrid quantum-classical algorithms for practical industry applications
- Lead R&D initiatives for quantum supremacy benchmarks in 2026 target domains
- Collaborate with hardware teams to optimize qubit coherence and gate fidelity
- Create quantum software development kits (SDKs) for enterprise adoption
- Establish security protocols for quantum-resistant encryption systems
- Mentor cross-functional teams in quantum computing principles
Qualifications
- PhD in Quantum Physics, Computer Science, or related field with 5+ years industry experience
- Expertise in quantum algorithms (Shor's, Grover's, VQE) and circuit optimization
- Proficiency in quantum programming languages (Q#, Qiskit, Cirq) and Python
- Deep understanding of quantum error correction and fault-tolerant architectures
- Published research in quantum computing or quantum information theory
- Experience with quantum hardware platforms (superconducting, trapped ion, photonic)
- Strong background in machine learning and high-performance computing