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Quantum AI Systems Architect

Nexus Quantum Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
20 Mei 2026
Deadline
20 Mei 2027

Job Description

Join Nexus Quantum Labs at the forefront of technological revolution as we pioneer quantum-AI hybrid systems that will redefine 2026's digital landscape. We seek a visionary architect to design next-generation computational frameworks that bridge quantum computing with artificial intelligence. In this role, you'll lead cross-disciplinary teams to develop scalable quantum neural networks and deploy fault-tolerant algorithms for real-world applications in cryptography, drug discovery, and climate modeling.

Our state-of-the-art facility in San Francisco offers unparalleled resources for breakthrough research, including access to 128-qubit processors and proprietary quantum simulators. You'll collaborate with Nobel laureates and industry pioneers to transform theoretical concepts into commercial solutions that will shape humanity's technological trajectory.

Responsibilities

  • Design quantum-AI hybrid architectures for enterprise-scale applications
  • Lead development of fault-tolerant quantum neural networks
  • Optimize quantum algorithms for machine learning acceleration
  • Collaborate with hardware teams to co-design quantum processors
  • Implement error correction protocols for scalable quantum systems
  • Translate theoretical research into production-ready solutions
  • Mentor junior researchers in quantum computing principles

Qualifications

  • PhD in Quantum Computing, Physics, or Computer Science
  • 5+ years experience in quantum algorithm development
  • Expertise in quantum error correction and fault tolerance
  • Proficiency with quantum programming languages (Q#, Qiskit)
  • Deep understanding of quantum machine learning frameworks
  • Published research in top-tier quantum computing journals
  • Strong background in high-performance computing architectures

Required Skills

Quantum Computing AI/ML Fault-Tolerant Systems Qiskit Q# Neural Networks Cryptography High-Performance Computing

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