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Quantum AI Systems Architect 2026

Nexus Quantum Dynamics
San Francisco
Estimated Salary
USD 250.000 – USD 350.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Join the forefront of technological evolution as a Quantum AI Systems Architect at Nexus Quantum Dynamics. We're pioneering the next generation of computational systems that will redefine human capability by 2026. In this pivotal role, you'll architect hybrid quantum-neural networks that solve previously unsolvable problems in medicine, climate science, and artificial intelligence. Our state-of-the-art labs in San Francisco offer unparalleled resources to transform theoretical breakthroughs into reality.

This position offers relocation assistance and equity in a company backed by visionary investors who understand that 2026 belongs to those who shape it today. You'll collaborate with Nobel laureates and Turing Award winners to create systems that will power humanity's next leap forward.

Responsibilities

  • Design and implement fault-tolerant quantum computing architectures for enterprise-scale AI applications
  • Develop hybrid quantum-classical machine learning pipelines processing exabyte-scale datasets
  • Create neural network compression techniques optimized for quantum coherence times
  • Lead cross-disciplinary teams of physicists, AI researchers, and hardware engineers
  • Architect quantum-resistant security protocols for next-gen communication networks
  • Prototype quantum algorithms solving NP-hard problems in real-world domains
  • Drive innovation in quantum error correction techniques at scale
  • Develop patent-pending quantum-AI integration methodologies

Qualifications

  • PhD in Quantum Computing, Theoretical Physics, or AI with 5+ years industry experience
  • Expertise in quantum algorithms (Shor's, Grover's, VQE) and error correction codes
  • Proficiency with quantum programming languages (Q#, Qiskit, Cirq) and classical ML frameworks
  • Published research in top-tier journals (Nature, Science, IEEE) on quantum-AI convergence
  • Experience architecting distributed systems processing petabyte-scale data
  • Demonstrated ability to lead technical teams through complex R&D projects
  • Deep understanding of quantum hardware limitations (qubit coherence, gate fidelity)
  • Track record of translating theoretical concepts into production-ready systems

Required Skills

Quantum Computing AI/ML Neural Networks Quantum Algorithms Error Correction Q# Qiskit Distributed Systems Exabyte Data Processing Hybrid Quantum-Classical Systems

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