Job Description
Join Nexus Future 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 systems that will revolutionize industries. This role offers unparalleled opportunities to work with cutting-edge hardware, collaborate with Nobel laureates, and shape the quantum landscape. Our Austin campus features state-of-the-art labs, flexible work arrangements, and comprehensive benefits including equity packages.
As part of our Innovation Accelerator program, you'll lead initiatives in quantum error correction, algorithm optimization, and hybrid quantum-classical workflows. We provide competitive relocation packages, professional development stipends, and access to our global research network. If you're passionate about solving humanity's most complex challenges through quantum technology, this is your moment to make history.
Responsibilities
- Design and implement scalable quantum computing architectures with 100+ qubit capabilities
- Develop hybrid quantum-classical workflows for enterprise applications
- Lead quantum error correction protocol optimization for fault-tolerant systems
- Collaborate with hardware teams on qubit coherence and gate fidelity improvements
- Create quantum algorithms for optimization, simulation, and cryptography applications
- Develop quantum cloud integration strategies for enterprise clients
- Mentor junior engineers and publish breakthrough research in peer-reviewed journals
Qualifications
- PhD in Quantum Physics, Computer Science, or related field (or equivalent experience)
- 5+ years experience in quantum computing architecture or algorithm development
- Proficiency in quantum programming languages (Qiskit, Cirq, Q#)
- Deep understanding of quantum error correction and fault-tolerance
- Experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)
- Published research in quantum computing or related fields
- Expertise in high-performance computing and parallel processing
- Strong background in linear algebra, probability theory, and information theory