Job Description
Join Nexus Future Labs at the forefront of 2026's technological revolution. We're seeking a pioneering Quantum Computing Architect to design next-gen computational frameworks that will redefine industries. As a key innovator in our Austin R&D hub, you'll architect scalable quantum systems, solve previously impossible computational challenges, and shape the future of artificial intelligence. This role offers unparalleled opportunities to work with cutting-edge hardware and collaborate with Nobel laureates in a culture that rewards bold experimentation and breakthrough thinking.
Your impact will extend beyond code – you'll contribute to patents, publish research in top-tier journals, and mentor the next generation of quantum pioneers. We provide comprehensive benefits including equity, flexible work arrangements, and a $20,000 annual tech stipend for continuous learning.
Responsibilities
- Design and implement fault-tolerant quantum algorithms for optimization, cryptography, and machine learning applications
- Architect hybrid quantum-classical computing frameworks leveraging 2026-era hardware capabilities
- Lead cross-functional teams of physicists and software engineers to prototype quantum solutions
- Develop error-correction protocols for million-qubit quantum processors
- Partner with industry leaders to implement quantum computing in finance, logistics, and healthcare
- Secure patents and publish breakthrough research in quantum information science
- Mentor junior researchers and establish best practices for quantum software development
Qualifications
- PhD in Quantum Computing, Physics, or Computer Science with 5+ years industry experience
- Expertise in quantum algorithms (Shor's, Grover's, VQE) and error correction techniques
- Proficiency in quantum programming languages (Q#, Qiskit, Cirq) and high-performance computing
- Published research in quantum information science or related top-tier journals
- Experience with cryogenic systems and quantum hardware integration
- Strong background in machine learning and classical optimization methods
- Demonstrated ability to lead technical teams and manage complex R&D projects