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Quantum Computing Architect 2026

Nexus Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Shape the future of computational science as a Quantum Computing Architect at Nexus Innovations. We're seeking a visionary leader to design next-generation quantum systems that will redefine technology by 2026. Join our elite team of researchers and engineers at the forefront of quantum supremacy, where your innovations will solve previously impossible problems across cryptography, AI, and materials science. Enjoy unparalleled resources, cutting-edge facilities, and a culture that rewards bold thinking. This is your opportunity to leave a permanent mark on human progress.

Responsibilities

  • Design scalable quantum algorithms for practical commercial applications by 2026
  • Lead R&D initiatives in quantum error correction and fault-tolerant systems
  • Collaborate with Nobel laureates to develop quantum-optimized machine learning frameworks
  • Secure $50M+ in government and private funding for quantum infrastructure
  • Architect hybrid quantum-classical computing solutions for Fortune 500 clients
  • Present breakthrough findings at IEEE Quantum Computing Summit
  • Mentor a team of 12 quantum physicists and software engineers

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field (or equivalent experience)
  • 5+ years developing quantum algorithms on real quantum processors
  • Published research in Nature/Science on quantum supremacy applications
  • Expertise in Qiskit, Cirq, or equivalent quantum programming frameworks
  • Proven track record of securing government SBIR grants
  • Experience with cryogenic quantum hardware integration
  • Deep understanding of quantum cryptography standards (NIST Post-Quantum Cryptography)
  • Portfolio of deployed quantum solutions solving real-world problems

Required Skills

Quantum Computing Quantum Algorithms Cryogenics Qiskit NIST Post-Quantum Cryptography Machine Learning R&D Management Scientific Publishing

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