Job Description
Join Nexus Labs at the forefront of technological evolution as we pioneer quantum computing solutions for 2026 and beyond. We're seeking a visionary Quantum Computing Architect to design next-gen quantum systems that will revolutionize industries. This role offers unparalleled opportunity to shape the future of computation in our state-of-the-art Austin research facility. Collaborate with Nobel laureates and industry pioneers to develop scalable quantum algorithms and error-correction frameworks. Your work will directly impact breakthrough applications in materials science, cryptography, and AI optimization.
We provide comprehensive benefits including equity, flexible work arrangements, and dedicated R&D funding. Our culture thrives on innovation, intellectual curiosity, and boundary-pushing research. If you're passionate about quantum mechanics and want to build systems that will define the next decade of computing, this is your calling.
Responsibilities
- Design scalable quantum computing architectures using superconducting qubits and topological systems
- Develop quantum error correction protocols for fault-tolerant operations
- Create hybrid quantum-classical algorithms for enterprise applications
- Lead cross-functional teams of physicists and software engineers
- Research and implement quantum machine learning frameworks
- Establish security protocols for quantum-encrypted communications
- Collaborate with hardware teams on qubit coherence optimization
Qualifications
- PhD in Quantum Physics, Computer Science, or related field (or equivalent experience)
- 3+ years in quantum algorithm development or quantum system design
- Proficiency with quantum programming languages (Q#, Qiskit, Cirq)
- Deep understanding of quantum decoherence and error correction
- Experience with superconducting qubit manipulation techniques
- Published research in quantum computing or quantum information theory
- Strong background in high-performance computing architectures
- Proven ability to translate theoretical concepts into practical implementations