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Quantum Computing Architect

NexusLabs
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Join NexusLabs at the forefront of technological revolution as we pioneer quantum computing solutions that will redefine industries by 2026. We seek a visionary Quantum Computing Architect to design next-generation quantum algorithms and systems that solve previously impossible computational challenges. You'll collaborate with Nobel laureates and lead a cross-disciplinary team to develop fault-tolerant quantum processors. This is your chance to shape the future of computation while enjoying Austin's vibrant tech ecosystem, competitive benefits, and unlimited professional growth.

Responsibilities

  • Design scalable quantum algorithms for optimization, cryptography, and machine learning applications
  • Lead the development of hybrid quantum-classical computing frameworks
  • Architect fault-tolerant quantum processor architectures with error correction protocols
  • Collaborate with hardware teams to translate theoretical models into physical implementations
  • Develop quantum security protocols for post-quantum encryption standards
  • Mentor junior researchers and publish breakthrough findings in top-tier journals
  • Secure strategic partnerships with quantum hardware manufacturers

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field (or equivalent industry experience)
  • 5+ years of experience in quantum algorithm design or quantum hardware development
  • Expertise in quantum programming languages (Qiskit, Cirq, or Q#)
  • Deep understanding of quantum error correction and fault-tolerance techniques
  • Proven track record of publishing peer-reviewed quantum computing research
  • Strong background in high-performance computing and parallel processing
  • Experience with cloud-based quantum platforms (IBM Quantum, Amazon Braket)

Required Skills

Quantum Computing Quantum Algorithms Fault Tolerance Cryptography Qiskit Cirq Q# Machine Learning High-Performance Computing

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